Computers Math

Scientists have created a cybersecurity technology called Shadow Figment that is designed to lure hackers into an artificial world, then stop them from doing damage by feeding them illusory tidbits of success.
The aim is to sequester bad actors by captivating them with an attractive — but imaginary — world.
The technology is aimed at protecting physical targets — infrastructure such as buildings, the electric grid, water and sewage systems, and even pipelines. The technology was developed by scientists at the U.S. Department of Energy’s Pacific Northwest National Laboratory.
The starting point for Shadow Figment is an oft-deployed technology called a honeypot — something attractive to lure an attacker, perhaps a desirable target with the appearance of easy access.
But while most honeypots are used to lure attackers and study their methods, Shadow Figment goes much further. The technology uses artificial intelligence to deploy elaborate deception to keep attackers engaged in a pretend world — the figment — that mirrors the real world. The decoy interacts with users in real time, responding in realistic ways to commands.
“Our intention is to make interactions seem realistic, so that if someone is interacting with our decoy, we keep them involved, giving our defenders extra time to respond,” said Thomas Edgar, a PNNL cybersecurity researcher who led the development of Shadow Figment. More

The myriad processes occurring in biological cells may seem unbelievably complex at first glance. And yet, in principle, they are merely a logical succession of events, and could even be used to form digital circuits. Researchers have now developed a molecular switching circuit made of DNA, which can be used to mechanically alter gels, depending on the pH. DNA-based switching circuits could have applications in soft robotics, say the researchers in their article in Angewandte Chemie.
DNA is a long molecule that can be folded and twisted in various ways. It has a backbone and bases that stick out from the backbone and pair up with counterparts in other DNA strands. When a series of these matching pairs comes together, they form a twisted, ladder-like double strand — the familiar DNA double helix. The flexibility of DNA, which makes it possible to produce bends, loops, and a wide variety of other shapes, has inspired researchers to build DNA switches. These switches change shape after receiving an input, and can then affect their surroundings.
Hao Pei from Shanghai Key Laboratory of Green Chemistry and Chemical Processes at the East China Normal University in Shanghai, China, and colleagues have now developed a configurable, multi-mode logic switching network that reacts differently with its surroundings depending on pH and DNA input. All the components of the switching circuit were produced from DNA.
The team developed a series of four DNA switches, each with slightly different lengths and combinations of bases. These variations meant they reacted differently with a single DNA strand depending on the pH of their surroundings. For example, at a slightly alkaline pH of 8, two of the switches formed triple-stranded DNA (triplexes), while the others remained loosely stretched out. These reactions and folds led to secondary reactions, which were utilized by the researchers as logic functions in the switching circuit. The result was, for example, a fluorescent signal that could be read as an output.
To demonstrate the use of the switching circuit in a real mechanical system, the team incorporated the DNA switches into polyacrylamide gels. The DNA acted as a crosslinker, joining the polymer molecules in the gel together. The shorter the crosslinker, or the more folded the DNA, the denser the gel became. Once a piece of DNA with matching bases was added as an input, a logic circuit was set in place, causing the DNA switches to unfold, form triplexes, or relax. The reaction circuit was also dependent on the pH. As a result, certain combinations of DNA input and pH range caused the DNA crosslinker to grow longer and the gel to swell up, in some cases nearly doubling in size.
As DNA switches have almost infinite possibilities for combinations of twists and folds, the researchers consider their switching circuits to be a vital step toward soft matter robotics, where controllable, miniaturized logic functional networks are important.
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Materials provided by Wiley. Note: Content may be edited for style and length. More

What makes cheetah the fastest land mammal? Why aren’t other animals, such as horses, as fast? While we haven’t yet figured out why, we have some idea about how — cheetahs, as it turns out, make use of a “galloping” gait at their fastest speeds, involving two different types of “flight”: one with the forelimbs and hind limbs beneath their body following a forelimb liftoff, called “gathered flight,” while another with the forelimbs and hind limbs stretched out after a hind limb liftoff, called “extended flight”. Of these, the extended flight is what enables cheetahs to accelerate to high speeds, and it depends on ground reaction forces satisfying specific conditions; in the case of horses, the extended flight is absent.
Additionally, cheetahs show appreciable spine movement during flight, alternating between flexing and stretching in gathered and extended modes, respectively, which contributes to its high-speed locomotion. However, little is understood about the dynamics governing these abilities.
“All animal running constitutes a flight phase and a stance phase, with different dynamics governing each phase,” explains Dr. Tomoya Kamimura from Nagoya Institute of Technology, Japan, who specializes in intelligent mechanics and locomotion. During the flight phase, all feet are in the air and the center of mass (COM) of the whole body exhibits ballistic motion. Conversely, during the stance phase, the body receives ground reaction forces through the feet. “Due to such complex and hybrid dynamics, observations can only get us so far in unraveling the mechanisms underlying the running dynamics of animals,” Dr. Kamimura says.
Consequently, researchers have turned to computer modeling to gain a better dynamic perspective of the animal gait and spine movement during running and have had remarkable success using fairly simple models. However, few studies so far have explored the types of flight and spine motion during galloping (as seen in a cheetah). Against this backdrop, Dr. Kamimura and his colleagues from Japan have now addressed this issue in a recent study published in Scientific Reports, using a simple model emulating vertical and spine movement.
The team, in their study, employed a two-dimensional model comprising two rigid bodies and two massless bars (representing the cheetah’s legs), with the bodies connected by a joint to replicate the bending motion of the spine and a torsional spring. Additionally, they assumed an anterior-posterior symmetry, assigning identical dynamical roles to the fore and hind legs.
By solving the simplified equations of motion governing this model, the team obtained six possible periodic solutions, with two of them resembling two different flight types (like cheetah galloping) and four, only one flight type (unlike cheetah galloping), based on the criteria related to the ground reaction forces provided by the solutions themselves. Researchers then verified these criteria with measured cheetah data, revealing that cheetah galloping in the real world indeed satisfied the criterion for two flight types through spine bending .
Additionally, the periodic solutions also revealed that horse galloping only involves gathered flight due to restricted spine motion, suggesting that the additional extended flight in cheetahs combined with spine bending allowed them to achieve such great speeds!
“While the mechanism underlying this difference in flight types between animal species still remains unclear, our findings extend the understanding of the dynamic mechanisms underlying high-speed locomotion in cheetahs. Furthermore, they can be applied to the mechanical and control design of legged robots in the future,” speculates an optimistic Dr. Kamimura.
Cheetahs inspiring legged robots! Who would’ve thought?
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Materials provided by Nagoya Institute of Technology. Note: Content may be edited for style and length. More

Can you trust the map on your smartphone, or the satellite image on your computer screen?
So far, yes, but it may only be a matter of time until the growing problem of “deep fakes” converges with geographical information science (GIS). Researchers such as Associate Professor of Geography Chengbin Deng are doing what they can to get ahead of the problem.
Deng and four colleagues — Bo Zhao and Yifan Sun at the University of Washington, and Shaozeng Zhang and Chunxue Xu at Oregon State University — co-authored a recent article in Cartography and Geographic Information Science that explores the problem. In “Deep fake geography? When geospatial data encounter Artificial Intelligence,” they explore how false satellite images could potentially be constructed and detected. News of the research has been picked up by countries around the world, including China, Japan, Germany and France.
“Honestly, we probably are the first to recognize this potential issue,” Deng said.
Geographic information science (GIS) underlays a whole host of applications, from national defense to autonomous cars, a technology that’s currently under development. Artificial intelligence has made a positive impact on the discipline through the development of Geospatial Artificial Intelligence (GeoAI), which uses machine learning — or artificial intelligence (AI) — to extract and analyze geospatial data. But these same methods could potentially be used to fabricate GPS signals, fake locational information on social media posts, fabricate photographs of geographic environments and more.
In short, the same technology that can change the face of an individual in a photo or video can also be used to make fake images of all types, including maps and satellite images. More

Researchers in Penn State’s College of Agricultural Sciences have developed a robotic mechanism for mushroom picking and trimming and demonstrated its effectiveness for the automated harvesting of button mushrooms.
In a new study, the prototype, which is designed to be integrated with a machine vision system, showed that it is capable of both picking and trimming mushrooms growing in a shelf system.
The research is consequential, according to lead author Long He, assistant professor of agricultural and biological engineering, because the mushroom industry has been facing labor shortages and rising labor costs. Mechanical or robotic picking can help alleviate those problems.
“The mushroom industry in Pennsylvania is producing about two-thirds of the mushrooms grown nationwide, and the growers here are having a difficult time finding laborers to handle the harvesting, which is a very labor intensive and difficult job,” said He. “The industry is facing some challenges, so an automated system for harvesting like the one we are working on would be a big help.”
The button mushroom — Agaricus bisporus — is an important agricultural commodity. A total of 891 million pounds of button mushrooms valued at $1.13 billion were consumed in the U.S. from 2017 to 2018. Of this production, 91% were for the fresh market, according to the U.S. Department of Agriculture, and were picked by hand, one by one, to ensure product quality, shelf life and appearance. Labor costs for mushroom harvesting account for 15% to 30% of the production value, He pointed out.
Developing a device to effectively harvest mushrooms was a complex endeavor, explained He. In hand-picking, a picker first locates a mature mushroom and detaches it with one hand, typically using three fingers. A knife, in the picker’s other hand, is then used to remove the stipe end. Sometimes the picker waits until there are two or three mushrooms in hand and cuts them one by one. Finally, the mushroom is placed in a collection box. A robotic mechanism had to achieve an equivalent picking process.
The researchers designed a robotic mushroom-picking mechanism that included a picking “end-effector” based on a bending motion, a “4-degree-of-freedom positioning” end-effector for moving the picking end-effector, a mushroom stipe-trimming end-effector, and an electro-pneumatic control system. They fabricated a laboratory-scale prototype to validate the performance of the mechanism.
The research team used a suction cup mechanism to latch onto mushrooms and conducted bruise tests on the mushroom caps to analyze the influence of air pressure and acting time of the suction cup.
The test results, recently published in Transactions of the American Society of Agricultural and Biological Engineers, showed that the picking end-effector was successfully positioned to the target locations and its success rate was 90% at first pick, increasing to 94.2% after second pick.
The trimming end-effector achieved a success rate of 97% overall. The bruise tests indicated that the air pressure was the main factor affecting the bruise level, compared to the suction-cup acting time, and an optimized suction cup may help to alleviate the bruise damage, the researchers noted. The laboratory test results indicated that the developed picking mechanism has potential to be implemented in automatic mushroom harvesting.
Button mushrooms for the study were grown in tubs at Penn State’s Mushroom Research Center on the University Park campus. Fabrication and experiments were conducted at the Fruit Research and Extension Center in Biglerville. A total of 70 picking tests were conducted to evaluate the robotic picking mechanism. The working pressures of the pneumatic system and the suction cup were set at 80 and 25 pounds per square inch, respectively.
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Materials provided by Penn State. Original written by Jeff Mulhollem. Note: Content may be edited for style and length. More

Simulators have long been used for training surgeons and surgical teams, but traditional simulator platforms typically have a built-in limitation: they often simulate one or a limited number of conditions that require performance of isolated tasks, such as placing an intravenous catheter, instead of simulating and providing opportunities for feedback on the performance of multiple interventions that a trauma victim may require at the same time. To overcome this limitation, the Advanced Modular Manikin (AMM), an innovative simulation platform that allows integration of other simulation devices, was developed and field testing was conducted, with support from the Department of Defense (DoD).
The DoD subcontracted with the American College of Surgeons (ACS) Division of Education to conduct field testing of the AMM. The results have been published online in advance of print by the Journal of the American College of Surgeons. Robert M. Sweet, MD, FACS, MAMSE, of the department of surgery at the University of Washington, served as principal investigator (PI) of the DoD contract to build the AMM. Ajit K. Sachdeva, MD, FACS, FRCSC, FSACME, MAMSE, Director, Division of Education, American College of Surgeons, served as the PI for the subcontract to conduct field testing.
The investigators reported that members of trauma teams at a testing site preferred the integrated AMM platform including a “peripheral” simulator over the “peripheral” simulator alone, in terms of realism, physiologic responses, and feedback they receive on the multiple and overlapping interventions they perform on a simulated trauma patient. Corresponding study author Dimitrios Stefanidis, MD, PhD, FACS, FASMBS, FSSH, of the department of surgery at Indiana University School of Medicine, Indianapolis, described the AMM as “more of a platform rather than a manikin.”
The DoD supported development of the AMM through a contract with the University of Minnesota and the University of Washington. The goal was to create an open-source simulation platform that permits integration of a number of simulators, known as “peripherals,” into a singular, comprehensive training platform. A Steering Committee composed of leaders and staff of the ACS Division of Education and the Research and Development Committee of the ACS-Accredited Education Institutes, along with leaders from the Development Team of the AMM Project created the model for field testing the AMM.
“The AMM platform, along with the ‘peripherals,’ can help to address the need for more robust simulators that focus on open procedures and interprofessional teamwork,” Dr. Sachdeva explained. “The ability to integrate the anatomic and physiologic elements of the simulation is an important advance. The experience with the trauma scenario may readily be extended to other surgical procedures and settings.”
Corresponding author Dr. Stefanidis explained that with most traditional simulators, instructors have to manipulate vital signs to respond to specific actions of the learner. He pointed out that the AMM promotes “a learner experience that is more based on the actual physiology of what’s happening to the patient.” The AMM platform allows different members of the trauma team to perform different tasks concurrently — one inserts a breathing tube, another starts an intravenous line, another performs a splenectomy. “All of these interventions impact the physiology,” he said.
The researchers evaluated team experience ratings of 14 trauma teams consisting of 42 individual members who performed tasks on the integrated AMM platform and the standalone “peripheral” simulator. Team experience ratings were higher for the integrated AMM platform as compared with the standalone “peripheral” simulator. Among the team members, surgeons and first responders rated their experience significantly higher than anesthesiologists, who noted higher workload ratings. In focus groups, the team members said they preferred the AMM platform because of its increased realism, and for the way it responded physiologically to their actions and the feedback it provided.
Dr. Stefanidis explained how the AMM can potentially aid in training trauma teams. “Trauma requires exemplary teamwork,” he said. “When we see patients who are injured, there are typically multiple providers who take care of them simultaneously — trauma surgeons, emergency room physicians, anesthesiologists, orthopedic surgeons, neurosurgeons, nurses, respiratory therapists, etc. So, it’s extremely important to also be able to train these teams in a low-stress simulation environment, such as by using the AMM, where they can hone their skills, individually and as a team, and perform at their best when faced with the very high-stress clinical environment.”
The AMM platform offers other benefits for improving the training and proficiency of trauma teams, said the field study PI, Dr. Sachdeva. “Specific training models could be standardized and the situation made increasingly complex in this safe simulation environment,” he said. More

University of South Florida researchers recently developed a novel approach to mitigating electromigration in nanoscale electronic interconnects that are ubiquitous in state-of-the-art integrated circuits. This was achieved by coating copper metal interconnects with hexagonal boron nitride (hBN), an atomically-thin insulating two-dimensional (2D) material that shares a similar structure as the “wonder material” graphene.
Electromigration is the phenomenon in which an electrical current passing through a conductor causes the atomic-scale erosion of the material, eventually resulting in device failure. Conventional semiconductor technology addresses this challenge by using a barrier or liner material, but this takes up precious space on the wafer that could otherwise be used to pack in more transistors. USF mechanical engineering Assistant Professor Michael Cai Wang’s approach accomplishes this same goal, but with the thinnest possible materials in the world, two-dimensional (2D) materials.
“This work introduces new opportunities for research into the interfacial interactions between metals and ångström-scale 2D materials. Improving electronic and semiconductor device performance is just one result of this research. The findings from this study opens up new possibilities that can help advance future manufacturing of semiconductors and integrated circuits,” Wang said. “Our novel encapsulation strategy using single-layer hBN as the barrier material enables further scaling of device density and the progression of Moore’s Law.” For reference, a nanometer is 1/60,000 of the thickness of human hair, and an ångström is one-tenth of a nanometer. Manipulating 2D materials of such thinness requires extreme precision and meticulous handling.
In their recent study published in the journal Advanced Electronic Materials, copper interconnects passivated with a monolayer hBN via a back-end-of-line (BEOL) compatible approach exhibited more than 2500% longer device lifetime and more than 20% higher current density than otherwise identical control devices. This improvement, coupled with the ångström-thinness of hBN compared to conventional barrier/liner materials, allows for further densification of integrated circuits. These findings will help advance device efficiency and decrease energy consumption.
“With the growing demand for electric vehicles and autonomous driving, the demand for more efficient computing has grown exponentially. The promise of higher integrated circuits density and efficiency will enable development of better ASICs (application-specific integrated circuits) tailored to these emerging clean energy needs.” explained Yunjo Jeong, an alumnus from Wang’s group and first author of the study.
An average modern car has hundreds of microelectronic components, and the significance of these tiny but critical components has been especially highlighted through the recent global chip shortage. Making the design and manufacturing of these integrated circuits more efficient will be key to mitigating possible future disruptions to the supply chain. Wang and his students are now investigating ways to speed up their process to the fab scale.
“Our findings are not limited only to electrical interconnects in semiconductor research. The fact that we were able to achieve such a drastic interconnect device improvement implies that 2D materials can also be applied to a variety of other scenarios.” Wang added.
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Materials provided by University of South Florida (USF Innovation). Note: Content may be edited for style and length. More

Quantum computing and quantum sensing have the potential to be vastly more powerful than their classical counterparts. Not only could a fully realized quantum computer take just seconds to solve equations that would take a classical computer thousands of years, but it could have incalculable impacts on areas ranging from biomedical imaging to autonomous driving.
However, the technology isn’t quite there yet.
In fact, despite widespread theories about the far-reaching impact of quantum technologies, very few researchers have been able to demonstrate, using the technology available now, that quantum methods have an advantage over their classical counterparts.
In a paper published on June 1 in the journal Physical Review X, University of Arizona researchers experimentally show that quantum has an advantage over classical computing systems.
“Demonstrating a quantum advantage is a long-sought-after goal in the community, and very few experiments have been able to show it,” said paper co-author Zheshen Zhang, assistant professor of materials science and engineering, principal investigator of the UArizona Quantum Information and Materials Group and one of the paper’s authors. “We are seeking to demonstrate how we can leverage the quantum technology that already exists to benefit real-world applications.”
How (and When) Quantum Works
Quantum computing and other quantum processes rely on tiny, powerful units of information called qubits. The classical computers we use today work with units of information called bits, which exist as either 0s or 1s, but qubits are capable of existing in both states at the same time. This duality makes them both powerful and fragile. The delicate qubits are prone to collapse without warning, making a process called error correction — which addresses such problems as they happen — very important. More