Computers Math

Legal documents, such as contracts or deeds, are notoriously difficult for nonlawyers to understand. A new study from MIT cognitive scientists has determined just why these documents are often so impenetrable.
After analyzing thousands of legal contracts and comparing them to other types of texts, the researchers found that lawyers have a habit of frequently inserting long definitions in the middle of sentences. Linguists have previously demonstrated that this type of structure, known as “center-embedding,” makes text much more difficult to understand.
While center-embedding had the most significant effect on comprehension difficulty, the MIT study found that the use of unnecessary jargon also contributes.
“It’s not a secret that legal language is very hard to understand. It’s borderline incomprehensible a lot of the time,” says Edward Gibson, an MIT professor of brain and cognitive sciences and the senior author of the new paper. “In this study, we’re documenting in detail what the problem is.”
The researchers hope that their findings will lead to greater awareness of this issue and stimulate efforts to make legal documents more accessible to the general public.
“Making legal language more straightforward would help people understand their rights and obligations better, and therefore be less susceptible to being unnecessarily punished or not being able to benefit from their entitled rights,” says Eric Martinez, a recent law school graduate and licensed attorney who is now a graduate student in brain and cognitive sciences at MIT. More

On the big screen, in video games and in our imaginations, lightsabers flare and catch when they clash together. In reality, as in a laser light show, the beams of light go through each other, creating spiderweb patterns. That clashing, or interference, happens only in fiction — and in places with enormous magnetic and electric fields, which happens in nature only near massive objects such as neutron stars. Here, the strong magnetic or electric field reveals that vacuum isn’t truly a void. Instead, here when light beams intersect, they scatter into rainbows.
A weak version of this effect has been observed in modern particle accelerators, but it is completely absent from our daily lives or even normal laboratory environments.
Yuli Lyanda-Geller, professor of physics and astronomy in the College of Science at Purdue University, in collaboration with Aydin Keser and Oleg Sushkov from the University of New South Wales in Australia, discovered that it is possible to produce this effect in a class of novel materials involving bismuth, its solid solutions with antimony and tantalum arsenide.
With this knowledge, the effect can be studied, potentially leading to vastly more sensitive sensors as well as supercapacitors for energy storage that could be turned on and off by a controlled magnetic field.
“Most importantly, one of the deepest quantum mysteries in the universe can be tested and studied in a small laboratory experiment,” Lyanda-Geller said. “With these materials, we can study effects of the universe. We can study what happens in neutron stars from our laboratories.”
Brief summary of methods
Keser, Lyanda-Geller and Sushkov applied quantum field theory nonperturbative methods used to describe high-energy particles and expanded them to analyze the behavior of so-called Dirac materials, which recently became the focus of interest. They used the expansion to obtain results that go both beyond known high-energy results and the general framework of condensed matter and materials physics. They suggested various experimental configurations with applied electric and magnetic fields and analyzed best materials that would allow them to experimentally study this quantum electrodynamic effect in a nonaccelerator setting.
They subsequently discovered that their results better explained some magnetic phenomena that had been observed and studied in earlier experiments.
Funding
U.S. Department of Energy, Office of Basic Energy Sciences; Division of Materials Sciences and Engineering; and the Australian Research Council, Centre of Excellence in Future Low Energy Electronics Technologies
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Materials provided by Purdue University. Original written by Brittany Steff. Note: Content may be edited for style and length. More

Computer engineers at Duke University have developed virtual eyes that simulate how humans look at the world accurately enough for companies to train virtual reality and augmented reality programs. Called EyeSyn for short, the program will help developers create applications for the rapidly expanding metaverse while protecting user data.
The results have been accepted and will be presented at the International Conference on Information Processing in Sensor Networks (IPSN), May 4-6, 2022, a leading annual forum on research in networked sensing and control.
“If you’re interested in detecting whether a person is reading a comic book or advanced literature by looking at their eyes alone, you can do that,” said Maria Gorlatova, the Nortel Networks Assistant Professor of Electrical and Computer Engineering at Duke.
“But training that kind of algorithm requires data from hundreds of people wearing headsets for hours at a time,” Gorlatova added. “We wanted to develop software that not only reduces the privacy concerns that come with gathering this sort of data, but also allows smaller companies who don’t have those levels of resources to get into the metaverse game.”
The poetic insight describing eyes as the windows to the soul has been repeated since at least Biblical times for good reason: The tiny movements of how our eyes move and pupils dilate provide a surprising amount of information. Human eyes can reveal if we’re bored or excited, where concentration is focused, whether or not we’re expert or novice at a given task, or even if we’re fluent in a specific language.
“Where you’re prioritizing your vision says a lot about you as a person, too,” Gorlatova said. “It can inadvertently reveal sexual and racial biases, interests that we don’t want others to know about, and information that we may not even know about ourselves.”
Eye movement data is invaluable to companies building platforms and software in the metaverse. For example, reading a user’s eyes allows developers to tailor content to engagement responses or reduce resolution in their peripheral vision to save computational power. More

By employing artificial intelligence (AI) and robotics to formulate therapeutic proteins, a team led by Rutgers researchers has successfully stabilized an enzyme able to degrade scar tissue resulting from spinal cord injuries and promote tissue regeneration.
The study, recently published in Advanced Healthcare Materials, details the team’s ground-breaking stabilization of the enzyme Chondroitinase ABC, (ChABC) offering new hope for patients coping with spinal cord injuries.
“This study represents one of the first times artificial intelligence and robotics have been used to formulate highly sensitive therapeutic proteins and extend their activity by such a large amount. It’s a major scientific achievement,” said Adam Gormley, the project’s principal investigator and an assistant professor of biomedical engineering at Rutgers School of Engineering (SOE) at Rutgers University-New Brunswick.
Gormley expressed that his research is also motivated, in part, by a personal connection to spinal cord injury.
“I’ll never forget being at the hospital and learning a close college friend would likely never walk again after being paralyzed from the waist down after a mountain biking accident,” Gormley recalled. “The therapy we are developing may someday help people such as my friend lessen the scar on their spinal cords and regain function. This is a great reason to wake up in the morning and fight to further the science and potential therapy.”
Shashank Kosuri, a biomedical engineering doctoral student at Rutgers SOE and a lead author of the study noted that spinal cord injuries, or SCIs, can negatively impact the physical, psychological, and socio-economic well-being of patients and their families. Soon after an SCI, a secondary cascade of inflammation produces a dense scar tissue that can inhibit or prevent nervous tissue regeneration.
The enzyme successfully stabilized in the study, ChABC, is known to degrade scar tissue molecules and promote tissue regeneration, yet it is highly unstable at the human body temperature of 98.6° F. and loses all activity within a few hours. Kosuri noted that this necessitates multiple, expensive infusions at very high doses to maintain therapeutic efficacy.
Synthetic copolymers are able to wrap around enzymes such as ChABC and stabilize them in hostile microenvironments. In order to stabilize the enzyme, the researchers utilized an AI-driven approach with liquid handling robotics to synthesize and test the ability of numerous copolymers to stabilize ChABC and maintain its activity at 98.6° F.
While the researchers were able to identify several copolymers that performed well, Kosuri reported that one copolymer combination even continued to retain 30% of the enzyme for up to one week, a promising result for patients seeking care for spinal cord injuries.
The study received support from grants funded by the National Institutes of Health, the National Science Foundation, and The New Jersey Commission on Spinal Cord research. In addition to Gormley and Kosuri, the Rutgers research team also included SOE Professor Li Cai and Distinguished Professor Martin Yarmush, as well as several SOE-affiliated students. Faculty and students from Princeton University’s Department of Chemical and Biological Engineering also collaborated on the project.
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Materials provided by Rutgers University. Original written by Emily Everson Layden. Note: Content may be edited for style and length. More

LSU physicists have leveraged quantum information theory techniques to reveal a mechanism for amplifying, or “stimulating,” the production of entanglement in the Hawking effect in a controlled manner. Furthermore, these scientists propose a protocol for testing this idea in the laboratory using artificially produced event horizons. These results have been recently published in Physical Review Letters, “Quantum aspects of stimulated Hawking radiation in an analog white-black hole pair,” where Ivan Agullo, Anthony J. Brady and Dimitrios Kranas present these ideas and apply them to optical systems containing the analog of a pair white-black hole.
Black holes are some of the most mystifying objects in our universe, largely due to the fact that their inner-workings are hidden behind a completely obscuring veil — the black hole’s event horizon.
In 1974, Stephen Hawking added more mystique to the character of black holes by showing that, once quantum effects are considered, a black hole isn’t really black at all but, instead, emits radiation, as if it was a hot body, gradually losing mass in the so-called “Hawking evaporation process.” Further, Hawking’s calculations showed that the emitted radiation is quantum mechanically entangled with the bowels of the black hole itself. This entanglement is the quantum signature of the Hawking effect. This astounding result is difficult, if not impossible, to be tested on astrophysical black holes, since the faint Hawking radiation gets overshined by other sources of radiation in the cosmos.
On the other hand, in the 1980’s, a seminal article by William Unruh established that the spontaneous production of entangled Hawking particles occurs in any system that can support an effective event horizon. Such systems generally fall under the umbrella of “analog gravity systems” and opened a window for testing Hawking’s ideas in the laboratory.
Serious experimental investigations into analog gravity systems — made of Bose-Einstein condensates, non-linear optical fibers, or even flowing water — have been underway for more than a decade. Stimulated and spontaneously-generated Hawking radiation has recently been observed in several platforms, but measuring entanglement has proved elusive due to its faint and fragile character.
“We show that, by illuminating the horizon, or horizons, with appropriately chosen quantum states, one can amplify the production of entanglement in Hawking’s process in a tunable manner,” said Associate Professor Ivan Agullo. “As an example, we apply these ideas to the concrete case of a pair of analog white-black holes sharing an interior and produced within a non-linear optical material.”
“Many of the quantum information tools used in this research were from my graduate research with Professor Jonathan P. Dowling,” said 2021 PhD alumnus Anthony Brady, postdoctoral researcher at the University of Arizona. “Jon was a charismatic character, and he brought his charisma and unconventionality into his science, as well as his advising. He encouraged me to work on eccentric ideas, like analog black holes, and see if I could meld techniques from various fields of physics — like quantum information and analog gravity — in order to produce something novel, or ‘cute,’ as he liked to say.”
“The Hawking process is one of the richest physical phenomena connecting seemingly unrelated fields of physics from the quantum theory to thermodynamics and relativity,” said Dimitrios Kranas, LSU graduate student. “Analog black holes came to add an extra flavor to the effect providing us, at the same time, with the exciting possibility of testing it in the laboratory. Our detailed numerical analysis allows us to probe new features of the Hawking process, helping us understand better the similarities and differences between astrophysical and analog black holes.”
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Materials provided by Louisiana State University. Note: Content may be edited for style and length. More

Researchers from the University of New Hampshire have mapped magnetic fields in three dimensions, a major step toward solving what they call the “grand challenge” of revealing 3D magnetic configuration in magnetic materials. The work has implications for improving diagnostic imaging and capacity in storage devices.
“The number three really represents a breakthrough in this field,” said Jiadong Zang, associate professor of physics. “Our brain is a three-dimensional object. It’s ironic that all our devices are two-dimensional. They’re underperforming compared to our brains.”
The study, published recently in the journal Nature Materials, provides the results of three years of high-performance numerical simulations, mapping a three-dimensional structure of a 100 nanometer magnetic tetrahedron sample using only three projection angles of electron beams. Zang points to computed tomography medical imaging, or CT scans, as an example. Instead of sending multiple beams of X-rays to map tissues in the body the same images could be produced with only three beams.
Reducing electron beam exposure in fast three-dimensional magnetic imaging is one potential application for this collaborative research. The researchers’ findings also have implications for improving storage capacity of magnetic memory devices, which currently deposit circuits onto two-dimensional panels that are approaching maximum density.
The method offered by this research will be a useful tool to detect and characterize three-dimensional magnetic circuits.
Zang and Alexander Booth, a former UNH doctoral student, conducted the theoretical analysis. Researchers from Japan and the University of Wisconsin performed the physical experiments. Funds from the U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES) under award number DE-SC0020221 helped support Zang and Booth’s contributions to this research.
The University of New Hampshire inspires innovation and transforms lives in our state, nation and world. More than 16,000 students from all 50 states and 71 countries engage with an award-winning faculty in top-ranked programs in business, engineering, law, health and human services, liberal arts and the sciences across more than 200 programs of study. A Carnegie Classification R1 institution, UNH partners with NASA, NOAA, NSF and NIH, and received $260 million in competitive external funding in FY21 to further explore and define the frontiers of land, sea and space.
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Materials provided by University of New Hampshire. Original written by Beth Potier. Note: Content may be edited for style and length. More

A new study has found that artificial intelligence (AI) apps helped protect small and medium-sized businesses against many of the risks that emerged during the COVID-19 pandemic — yet only a quarter of small firms currently use them.
The research, undertaken by Anglia Ruskin University (ARU) and published in the journal Information Systems Frontiers, surveyed 317 small and medium sized firms based in London. The study found the use of AI-powered apps was associated with a 3.1% reduced risk to business during the pandemic.
The COVID-19 pandemic has created risks for economies and business operations, with customers stopping, reducing, or postponing purchases, thereby affecting supply chains and resulting in difficulties in sourcing alternative suppliers.
Business risks were defined by a 60-point scale developed by the International Labor Organization’s (ILO) that measures the pandemic’s impact on staffing, processes such as working patterns, reduced profits, and threats to partnerships.
AI software utilised by businesses include chatbots to allow swift interaction with customers, apps that identify damaging fake reviews, and apps that use algorithms to improve customer targeting based on their habits, social media activities and profiles, online activities, and past transactions.
The study found the use of AI apps to offer personalised shopping suggestions was associated with 2% lower business risks to profits caused by the COVID-19 pandemic. The use of AI apps to target audience online was associated with 1.2% lower overall business risk.
However, the research revealed that only 26% of small enterprises were utilising AI applications, considerably lower than the 70.4% of medium-sized businesses.
Lead author Professor Nick Drydakis, Director of the Centre for Pluralist Economics at Anglia Ruskin University, said: “SMEs can invest in AI technologies to track users’ habits and provide recommendations, improve customer’s purchasing decisions, search results, media communication, trade raise sales, improve organisational performance, and lower costs.
“AI can help SMEs to adapt to unprecedented conditions, meaning they can leverage technology to meet new types of demand, move at speed to pivot business operations, boost efficiency and reduce their business risks.
“We found that SMEs’ business risks caused by the COVID-19 pandemic declined with the use of AI applications across a ten-item scale including marketing, sales, communication, predictions, pricing and cash flow, fake reviews, cybersecurity, recruitment, and legal services.
“The outcomes proved true regardless of enterprise size, turnover, and years of operation, indicating that AI applications have helped SMEs to adapt to unprecedented conditions during the COVID-19 pandemic.
“It seems investment in AI apps could be a smart move for the three quarters of small businesses that do not currently utilise them.” More

The flexible arm, which was designed and created at Imperial College London, can twist and turn in all directions, making it readily customisable for potential applications in manufacturing, spacecraft maintenance, and even injury rehabilitation.
Instead of being constrained by rigid limbs and firm joints, the versatile arm is readily bendable into a wide variety of shapes. In practice, people working alongside the robot would manually bend the arm into the precise shape needed for each task, a level of flexibility made possible by the slippery layers of mylar sheets inside, which slide over one another and can lock into place. However, configuring the robot into specific shapes without guidance has proven to be difficult for users.
To enhance the robot’s user-friendliness, researchers at Imperial’s REDS (Robotic manipulation: Engineering, Design, and Science) Lab have designed a system for users to see in AR how to configure their robot. Wearing mixed reality smartglasses and through motion tracking cameras, users see templates and designs in front of them superimposed onto their real-world environment. They then adjust the robotic arm until it matches the template, which turns green on successful configuration so that the robot can be locked into place.
Senior author of the paper Dr Nicolas Rojas, of Imperial’s Dyson School of Design Engineering, said: “One of the key issues in adjusting these robots is accuracy in their new position. We humans aren’t great at making sure the new position matches the template, which is why we looked to AR for help.
“We’ve shown that AR can simplify working alongside our malleable robot. The approach gives users a range of easy-to-create robot positions, for all sorts of applications, without needing so much technical expertise.”
The researchers tested the system on five men aged 20-26 with experience in robotics but no experience with manipulating malleable robots specifically. The subjects were able to adjust the robot accurately, and the results are published in Robotics & Automation Magazine.
Although the pool of participants was narrow, the researchers say their initial findings show that AR could be a successful approach to adapting malleable robots following further testing and user training.
Bent into shape
Potential applications include manufacturing, and building and vehicle maintenance. Because the arm is lightweight, it could also be used on spacecraft where low-weight instruments are preferred. It is also gentle enough that it could be used in injury rehabilitation, helping a patient perform an exercise while their physiotherapist performs another.
Co-first authors PhD researchers Alex Ranne and Angus Clark, also of the Dyson School of Design Engineering, said: “In many ways it can be seen as a detached, bendier, third arm. It could help in many situations where an extra limb might come in handy and help to spread the workload.”
The researchers are still in the process of perfecting the robot as well as its AR component. Next, they will look into introducing touch and audio elements to the AR to boost its accuracy in configuring the robot.
They are also looking into strengthening the robots. Although their flexibility and softness makes them easier to configure and maybe even safer to work alongside humans, they are less rigid while in the locked position, which could affect precision and accuracy.
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Materials provided by Imperial College London. Original written by Caroline Brogan. Note: Content may be edited for style and length. More