Computers Math

During the swarming of birds or fish, each entity coordinates its location relative to the others, so that the swarm moves as one larger, coherent unit. Fireflies on the other hand coordinate their temporal behavior: within a group, they eventually all flash on and off at the same time and thus act as synchronized oscillators.
Few entities, however, coordinate both their spatial movements and inherent time clocks; the limited examples are termed “swarmalators”1, which simultaneously swarm in space and oscillate in time. Japanese tree frogs are exemplar swarmalators: each frog changes both its location and rate of croaking relative to all the other frogs in a group.
Moreover, the frogs change shape when they croak: the air sac below their mouth inflates and deflates to make the sound. This coordinated behavior plays an important role during mating and hence, is vital to the frogs’ survival. In the synthetic realm there are hardly any materials systems where individual units simultaneously synchronize their spatial assembly, temporal oscillations and morphological changes. Such highly self-organizing materials are important for creating self-propelled soft robots that come together and cooperatively alter their form to accomplish a regular, repeated function.
Chemical engineers at the University of Pittsburgh Swanson School of Engineering have now designed a system of self-oscillating flexible materials that display a distinctive mode of dynamic self-organization. In addition to exhibiting the swarmalator behavior, the component materials mutually adapt their overall shapes as they interact in a fluid-filled chamber. These systems can pave the way for fabricating collaborative, self-regulating soft robotic systems.
The group’s research was published this week in the journal Proceedings of the National Academy of Sciences. Principal investigator is Anna C. Balazs, Distinguished Professor of Chemical and Petroleum Engineering and the John A. Swanson Chair of Engineering. Lead author is Raj Kumar Manna and co-author is Oleg E. Shklyaev, both post-doctoral associates.
“Self-oscillating materials convert a non-periodic signal into the material’s periodic motion,” Balazs explained. “Using our computer models, we first designed micron and millimeter sized flexible sheets in solution that respond to a non-periodic input of chemical reactants by spontaneously undergoing oscillatory changes in location, motion and shape. For example, an initially flat, single sheet morphs into a three-dimensional shape resembling an undulating fish tail, which simultaneously oscillates back and forth across the microchamber.”
The self-oscillations of the flexible sheets are powered by catalytic reactions in a fluidic chamber. The reactions on the surfaces of the sheet and chamber initiate a complex feedback loop: chemical energy from the reaction is converted into fluid flow, which transports and deforms the flexible sheets. The structurally evolving sheets in turn affect the motion of the fluid, which continues to deform the sheets.
“What is really intriguing is that when we introduce a second sheet, we uncover novel forms of self-organization between vibrating structures,” Manna adds. In particular, the two sheets form coupled oscillators that communicate through the fluid to coordinate not only their location and temporal pulsations, but also synchronize their mutual shape changes. This behavior is analogous to that of the tree frog swarmalators that coordinate their relative spatial location, and time of croaking, which also involves a periodic change in the frog’s shape (with an inflated or deflated throat).
“Complex dynamic behavior is a critical feature of biological systems,” Shklyaev says. Stuff does not just come together and stop moving. Analogously, these sheets assemble in the proper time and space to form a larger, composite dynamic system. Moreover, this structure is self-regulating and can perform functions that a single sheet alone cannot carry out.”
“For two or more sheets, the collective temporal oscillations and spatial behavior can be controlled by varying the size of the different sheets or the pattern of catalyst coating on the sheet,” says Balazs. These variations permit control over the relative phase of the oscillations, e.g., the oscillators can move in-phase or anti-phase.
“These are very exciting results because the 2D sheets self-morph into 3D objects, which spontaneously translate a non-oscillating signal into “instructions” for forming a larger aggregate whose shape and periodic motion is regulated by each of its moving parts,” she notes. “Our research could eventually lead to forms of bio-inspired computation — just as coupled oscillators are used to transmit information in electronics — but with self-sustained, self-regulating behavior.”
Video: https://www.youtube.com/watch?v=89Y9lVlEaBs More

Wealthier northeastern US states and Western European countries tended to have significantly lower mortality rates during second-wave COVID-19 infections, new research from the University of Sydney and Tsinghua University has shown. However, the pattern was not as general as expected, with notable exceptions to this trend in Sweden and Germany.
Researchers say mortality change could have several explanations: European first-wave case counts were underestimated; First-wave deaths disproportionately affected the elderly; Second-wave infections tended to affect younger people; With some exceptions, lower mortality rates occurred in countries with more socialised and equitable health systems.The researchers, Nick James, Max Menzies and Peter Radchenko, believe their new methodology could assist epidemiologists to analyse data consistently to assess the impact of COVID-19 mortality across populations.
“We have been able to look at the mortality rates in a more dynamic way,” said Mr James from the University of Sydney.
They have published their results today in the mathematical journal Chaos.
“We take a time series of infection rates by country, apply an algorithmic approach to chop it up into first and later waves and then do some relatively simple optimisation and calculations to determine two different mortality numbers,” said Nick James, a PhD student in the School of Mathematics & Statistics at the University of Sydney. More

A Florida State University professor’s research could help quantum computing fulfill its promise as a powerful computational tool.
William Oates, the Cummins Inc. Professor in Mechanical Engineering and chair of the Department of Mechanical Engineering at the FAMU-FSU College of Engineering, and postdoctoral researcher Guanglei Xu found a way to automatically infer parameters used in an important quantum Boltzmann machine algorithm for machine learning applications.
Their findings were published in Scientific Reports.
The work could help build artificial neural networks that could be used for training computers to solve complicated, interconnected problems like image recognition, drug discovery and the creation of new materials.
“There’s a belief that quantum computing, as it comes online and grows in computational power, can provide you with some new tools, but figuring out how to program it and how to apply it in certain applications is a big question,” Oates said.
Quantum bits, unlike binary bits in a standard computer, can exist in more than one state at a time, a concept known as superposition. Measuring the state of a quantum bit — or qubit — causes it to lose that special state, so quantum computers work by calculating the probability of a qubit’s state before it is observed.
Specialized quantum computers known as quantum annealers are one tool for doing this type of computing. They work by representing each state of a qubit as an energy level. The lowest energy state among its qubits gives the solution to a problem. The result is a machine that could handle complicated, interconnected systems that would take a regular computer a very long time to calculate — like building a neural network.
One way to build neural networks is by using a restricted Boltzmann machine, an algorithm that uses probability to learn based on inputs given to the network. Oates and Xu found a way to automatically calculate an important parameter associated with effective temperature that is used in that algorithm. Restricted Boltzmann machines typically guess at that parameter instead, which requires testing to confirm and can change whenever the computer is asked to investigate a new problem.
“That parameter in the model replicates what the quantum annealer is doing,” Oates said. “If you can accurately estimate it, you can train your neural network more effectively and use it for predicting things.”
This research was supported by Cummins Inc. and used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility.
Story Source:
Materials provided by Florida State University. Original written by Bill Wellock. Note: Content may be edited for style and length. More

Superconductivity is a complete loss of electrical resistance. Superconductors are not merely very good metals: it is a fundamentally different electronic state. In normal metals, electrons move individually, and they collide with defects and vibrations in the lattice. In superconductors, electrons are bound together by an attractive force, which allows them to move together in a correlated way and avoid defects.
In a very small number of known superconductors, the onset of superconductivity causes spontaneous electrical currents to flow. These currents are very different from those in a normal metal wire: they are built into the ground state of the superconductor, and so they cannot be switched off. For example, in a sheet of a superconducting material, currents might appear that flow around the edge, as shown in the figure.
This is a very rare form of superconductivity, and it always indicates that the attractive interaction is something unusual. Sr2RuO4 is one famous material where this type of superconductivity is thought to occur. Although the transition temperature is low — Sr2RuO4 superconducts only below 1.5 Kelvin — the reason why it superconducts at all is completely unknown. To explain the superconductivity in this material has become a major test of physicists’ understanding of superconductivity in general. Theoretically, it is very difficult to obtain spontaneous currents in Sr2RuO4 from standard models of superconductivity, and so if they are confirmed then a new model for superconductivity — an attractive force that is not seen in other materials — might be required.
The way that these electrical currents are detected is subtle. Subatomic particles known as muons are implanted into the sample. The spin of each muon then precesses in whatever magnetic field exists at the muon stopping site. In effect, the muons act as sensitive detectors of magnetic field, that can be placed inside the sample. From such muon implantation experiments it has been found that spontaneous magnetic fields appear when Sr2RuO4 becomes superconducting, which shows that there are spontaneous electrical currents.
However, because the signal is subtle, researchers have questioned whether it is in fact real. Onset of superconductivity is a major change in the electronic properties of a material, and maybe this subtle additional signal appeared because the measurement apparatus was not properly tuned.
In this work, researchers at the Max Planck Institute for Chemical Physics of Solids, the Technical University of Dresden, and the Paul Scherrer Institute (Switzerland) have shown that when uniaxial pressure is applied to Sr2RuO4, the spontaneous currents onset at a lower temperature than the superconductivity. In other words, the transition splits into two: first superconductivity, then spontaneous currents. This splitting has not been clearly demonstrated in any other material, and it is important because it shows definitively that the second transition is real. The spontaneous currents must be explained scientifically, not as a consequence of imperfect measurement. This may require a major re-write of our understanding of superconductivity.
Story Source:
Materials provided by Max Planck Institute for Chemical Physics of Solids. Note: Content may be edited for style and length. More

Researchers from Louisiana State University have introduced a smart quantum technology for the spatial mode correction of single photons. In a paper featured on the cover of the March 2021 issue of Advanced Quantum Technologies, the authors exploit the self-learning and self-evolving features of artificial neural networks to correct the distorted spatial profile of single photons.
The authors, PhD candidate Narayan Bhusal, postdoctoral researcher Chenglong You, graduate student Mingyuan Hong, undergraduate student Joshua Fabre, and Assistant Professor Omar S. Magaña?Loaiza of LSU — together with collaborators Sanjaya Lohani, Erin M. Knutson, and Ryan T. Glasser of Tulane University and Pengcheng Zhao of Qingdao University of Science and Technology — report on the potential of artificial intelligence to correct spatial modes at the single-photon level.
“The random phase distortion is one of the biggest challenges in using spatial modes of light in a wide variety of quantum technologies, such as quantum communication, quantum cryptography, and quantum sensing,” said Bhusal. “In this paper, we use artificial neurons to correct distorted spatial modes of light at the single-photon level. Our method is remarkably effective and time-efficient compared to conventional techniques. This is an exciting development for the future of free-space quantum technologies.”
The newly developed technique boosts the channel capacity of optical communication protocols that rely on structured photons.
“One important goal of the Quantum Photonics Group at LSU is to develop robust quantum technologies that work under realistic conditions,” said Magaña?Loaiza. “This smart quantum technology demonstrates the possibility of encoding multiple bits of information in a single photon in realistic communication protocols affected by atmospheric turbulence. Our technique has enormous implications for optical communication and quantum cryptography. We are now exploring paths to implement our machine learning scheme in the Louisiana Optical Network Initiative (LONI) to make it smart, secure, and quantum.”
“We are still in the fairly early stages of understanding the potential for machine learning techniques to play a role in quantum information science,” said Dr. Sara Gamble, program manager at the Army Research Office, an element of DEVCOM ARL. “The team’s result is an exciting step forward in developing this understanding, and it has the potential to ultimately enhance the Army’s sensing and communication capabilities on the battlefield.”
Story Source:
Materials provided by Louisiana State University. Note: Content may be edited for style and length. More

Just one year after the World Health Organization declared the novel coronavirus a global pandemic, three COVID-19 vaccines are available in the United States, and more than 2 million Americans are receiving shots each day. Americans are eager to get back to business as usual, but experts caution that opening the economy prematurely could allow a potential resurgence of the virus. How foot traffic patterns in restaurants and bars, schools and universities, nail salons and barbershops affect the risk of transmission has been largely unknown.
In an article published in npj Digital Medicine, researcher-physicians from Beth Israel Deaconess Medical Center (BIDMC) used anonymized cell-phone data to build a Business Risk Index, which quantifies the potential risk of COVID-19 transmission in these establishments. The team’s index accounts for both the density of visits and the length of time individuals linger inside, providing a more precise description of the human interactions — and thus risk of viral transmission — going on inside.
“While business traffic pre-pandemic and during statewide shut downs has been studied, business foot traffic and its relationship to COVID-19 transmission in the so-called ‘new normal’ of re-opening has not been well understood.” said corresponding author Ashley O’Donoghue, PhD, Economist, in the Center for Healthcare Delivery Science at BIDMC. “Many forecasting models use anonymized cell-phone mobility data as a broad measure of the movement of residents. But two regions with same levels of mobility will likely see very different levels of COVID-19 transmission if people in one region are diligently practicing social distancing and people in the other are not.”
O’Donoghue and colleagues built their risk index by analyzing trends in foot traffic patterns in more than 1.25 million businesses across eight states from January to June 2020. In the six New England states, New York and California, the team saw a 30 percent drop in high-density foot traffic and long visit lengths to businesses — two factors that can increase the risk of COVID-19 transmission — from the pre-pandemic baseline to April 2020. They saw similar declines when they looked at similar risky foot traffic patterns in restaurants, bars, universities and personal care establishments (which includes hair and nail salons and barbershops). In both analyses, the risk index rose steadily starting in mid-June as states eased restrictions.
Next, using county-level COVID-19 data for the same time period, the team demonstrated that their index could accurately forecast future COVID-19 cases with a one-week lag. The team found that an increase in a county’s average Business Risk Index was associated with an increase in COVID-19 cases per 10,000 people in one week.
“Not all types of mobility contribute equally to increased risk of transmission, so it is important to directly measure human interaction when weighing the costs and benefits of reopening and lifting restrictions on businesses,” said senior author Jennifer P. Stevens, MD, MS, Director of the Center for Healthcare Delivery Science at BIDMC. “Tracking how individuals use different businesses may provide the kind of information policymakers need to re-open different businesses in the safest way possible.”
O’Donoghue, Stevens and team are now building an online decision-support tool that will help policymakers and hospital decision-makers monitor weekly risk in their areas. They have also deployed a prototype of their tool for Massachusetts that is being used by a large tertiary academic medical center in Boston to monitor potential surges in their service area, and their index has been integrated as a feature in a forecasting model for a large health system in Massachusetts.
“Our index can better quantify close human interactions, which are important predictors of transmission and help identify potential disease surges,” said Stevens.
Study co-authors also include Tenzin Dechen, MPH, of BIDMC; Whitney Pavlova, BA, of Pennsylvania State University; Michael Boals, MS, of Requisite Analytics; Manvi Madan, MInfoTech, of Ports of Auckland; Garba Moussa, PhD, of Open-Classroom; Aalok Thakkar, BS, of University of Pennsylvania; and Frank J. DeFalco, BS, of Janssen Research & Development.
Dr. Stevens is supported by grant number K08HS024288 from the Agency for Healthcare Research and Quality. The authors declare no competing interests. More

Trillions of commensal microbes live on the mucosal and epidermal surfaces of the body and it is firmly established that this microbiome affects its host’s tolerance and sensitivity of the host to a variety of pathogens. However, host tolerance to infection with pathogens is not equally developed in all organisms. For example, it is known that the gut microbiome of mice protects more effectively against infection with certain pathogens, such as the bacterium Salmonella typhimurium, than the human gut microbiome.
This raises the interesting possibility that analyzing differences between host-microbiome interactions in humans and other species, such as mice, and pinpointing individual types of bacterial that either protect or sensitize against certain pathogens, could lead to entirely new types of therapeutic approaches. However, while the intestinal microbiome composition and its effect on host immune responses have been well investigated in mice, it is not possible to study how the microbiome interacts directly with the epithelial cells lining the intestine under highly defined conditions, and thereby uncover specific bacterial strains that can induce host-tolerance to infectious pathogens.
Now, a collaborative team led by Wyss Founding Director Donald Ingber, M.D., Ph.D. at Harvard’s Wyss Institute for Biologically Inspired Engineering and Dennis Kasper, M.D. at Harvard Medical School (HMS) has harnessed the Wyss’s microfluidic Organs-on-Chip (Organ Chip) technology to model the different anatomical sections of the mouse intestine and their symbiosis with a complex living microbiome in vitro. The researchers recapitulated the destructive effects of S. typhimurium on the intestinal epithelial surface in an engineered mouse Colon Chip, and in a comparative analysis of mouse and human microbiomes were able to confirm the commensal bacterium Enterococcus faecium contributes to host tolerance to S. typhimurium infection. The study is published in Frontiers in Cellular and Infection Microbiology.
The project was started under a DARPA-supported “Technologies for Host Resilience” (THoR) Project at the Wyss Institute, whose goal it was to uncover key contributions to tolerance to infection by studying differences observed in certain animal species and humans. Using a human Colon Chip, Ingber’s group had shown in a previous study how metabolites produced by microbes derived from mouse and human feces have different potential to impact susceptibility to infection with an enterohemorrhagic E. coli pathogen.
“Biomedical research strongly depends on animal models such as mice, which undoubtedly have tremendous benefits, but do not provide an opportunity to study normal and pathological processes within a particular organ, such as the intestine, close-up and in real-time. This important proof-of-concept study with Dennis Kasper’s group highlights that our engineered mouse Intestine Chip platform offers exactly this capability and provides the possibility to study host-microbiome interactions with microbiomes from different species under highly controllable conditions in vitro,” said Ingber. “Given the deep level of characterization of mouse immunology, this capability could greatly help advance the work of researchers who currently use these animals to do research on microbiome and host responses. It enables them to compare their results they obtain directly with human Intestine Chips in the future so that the focus can be on identifying features of host response that are most relevant for humans.” Ingber also is the Judah Folkman Professor of Vascular Biology at HMS and Boston Children’s Hospital, and Professor of Bioengineering at the Harvard John A. Paulson School of Engineering and Applied Sciences.
Engineering a mouse Intestine-on-Chip platform
In their new study, the team focused on the mouse intestinal tract. “It has traditionally been extremely difficult to model host-microbiome interactions outside any organism as many bacteria are strictly anaerobic and die in normal atmospheric oxygen conditions. Organ Chip technology can recreate these conditions, and it is much easier to obtain primary intestinal and immune cells from mice than having to rely on human biopsies,” said first-author Francesca Gazzaniga, Ph.D., a Postdoctoral Fellow who works between Ingber’s and Kasper’s groups and spear-headed the project.

advertisement

Gazzaniga and her colleagues isolated intestinal crypts from different regions of the mouse intestinal tract, including the duodenum, jejunum, ileum, and colon, took their cells through an intermediate “organoid” step in culture in which small tissue fragments form and grow, which they then seeded into one of two parallel microfluidically perfused channels of the Wyss’ Organ Chips to create region-specific Intestine Chips. The second independently perfused channel mimics the blood vasculature, and is separated from the first by a porous membrane that allows the exchange of nutrients, metabolites, and secreted molecules that intestinal epithelial cells use to communicate with vascular and immune cells.
Homing in on the pathogen
The team then honed in on S. typhimurium as a pathogen. First, they introduced the pathogen into the epithelial lumen of the engineered mouse Colon Chip and recapitulated the key features associated with the break-down of intestinal tissue integrity known from mouse studies, including the disruption of normally tight adhesions between neighboring epithelial cells, decreased production of mucus, a spike in secretion of a key inflammatory chemokine (the mouse homolog of human IL-8), and changes in epithelial gene expression. In parallel, they showed that the mouse Colon Chip supported the growth and viability of complex bacterial consortia normally present in mouse and human gut microbiomes.
Putting these capabilities together, the researchers compared the effects of specific mouse and human microbial consortia that had previously been maintained stably in the intestines of ‘gnotobiotic’ mice that were housed in germ-free conditions by the Kasper team. By collecting complex microbiomes from the stool of those mice, and then inoculating them into the Colon Chips, the researchers observed chip-to-chip variability in consortium composition, which enabled them to relate microbe composition to functional effects on the host epithelium. “Using 16s sequencing gave us a good sense of the microbial compositions of the two consortia, and high numbers of one individual species, Enterococcus faecium, generated by only one of them in the Colon Chip, allowed the intestinal tissue to better tolerate the infection,” said Gazzaniga. “This nicely confirmed past findings and validated our approach as a new discovery platform that we can now use to investigate the mechanisms that underlie these effects as well as the contribution of vital immune cell contributions to host-tolerance, as well as infectious processes involving other pathogens.”
“The mouse intestine on a chip technology provides a unique approach to understand the relationship between the gut microbiota, host immunity, and a microbial pathogen. This important interrelationship is challenging to study in the living animal because there are so many uncontrollable factors. The beauty of this system is that essentially all parameters you wish to study are controllable and can easily be monitored. This system is a very useful step forward,” said Kasper, who is the William Ellery Channing Professor of Medicine and Professor of Immunology at HMS.
The researchers believe that their comparative in vitro approach could uncover specific cross-talk between pathogens and commensal bacteria with intestinal epithelial and immune cells, and that identified tolerance-enhancing bacteria could be used in future therapies, which may circumvent the problem increasing antimicrobial resistance of pathogenic bacterial strains. More

Increased internet-access spending by Texas public schools improved academic performance but also led to more disciplinary problems among students, a study of 9,000 schools conducted by a research team from Rice University, Texas A&M University and the University of Notre Dame shows.
Whether students benefit from increased internet access in public schools has been an open question, according to the researchers. For example, some parents and policy advocates contend it increases children’s access to obscene or harmful content and disciplinary problems. Others believe it promotes personalized learning and higher student engagement.
To address these policy questions, the research team created a multiyear dataset (2000-14) of 1,243 school districts representing more than 9,000 Texas public schools. The team measured internet-access spending, 11 academic performance indicators and 47 types of school disciplinary problems. It used econometric techniques to develop causal estimates linking internet-access spending to academic performance and disciplinary problems. Using student earning, the researchers calculated the economic impact of increased annual internet spending.
To date, this is the largest and most comprehensive study linking school internet-access spending to academic and disciplinary outcomes, the researchers said.
The team found that increased school district internet spending is associated with not only improved graduation rates, but also higher numbers of students meeting SAT/ACT criterion and completing advanced courses. It also led to an improvement in commended performance in math, reading, writing and social studies. Interestingly, the researchers noted these improvements were stronger for students who lived in counties with greater internet access (as measured by the number of broadband providers).
On the flip side, increased school district internet spending also led to higher rates of disciplinary problems at schools, they said.
The team also calculated how much economic benefit a school district’s internet access will bring students during their lifetimes. It found that a $600,000 increase in annual internet-access spending produces a financial gain of approximately $820,000 to $1.8 million per school district, together with losses from disciplinary problems totaling $25,800 to $53,440.
In other words, investments in internet access are well worth the costs.
“We are proud that Texas public schools can serve as a live learning case for understanding education policy,” said study co-author Vikas Mittal, a professor of marketing at Rice’s Jones Graduate School of Business. “Investments in internet access provide clear and meaningful academic benefits. Yet, schools need to implement policies to address increased disciplinary issues such as cyberbullying.
“K-12 education has transformed into virtual learning due to COVID-19,” he continued. “Our research conclusions apply to a setting where physical learning is supplemented by internet access.”
However, Mittal cautioned that these benefits cannot be expected to hold if physical learning is completely supplanted by internet-based learning.

Story Source:
Materials provided by Rice University. Note: Content may be edited for style and length. More