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Technology review


We just got our best-ever look at the inside of Mars

NASA’s InSight robotic lander has just given us our first look deep inside a planet other than Earth. 

More than two years after its launch, seismic data that InSight collected has given researchers hints into how Mars was formed, how it has evolved over 4.6 billion years, and how it differs from Earth. A set of three new studies, published in Science this week, suggests that Mars has a thicker crust than expected, as well as a molten liquid core that is bigger than we thought.  

In the early days of the solar system, Mars and Earth were pretty much alike, each with a blanket of ocean covering the surface. But over the following 4 billion years, Earth became temperate and perfect for life, while Mars lost its atmosphere and water and became the barren wasteland we know today. Finding out more about what Mars is like inside might help us work out why the two planets had such very different fates. 

“By going from [a] cartoon understanding of what the inside of Mars looks like to putting real numbers on it,” said Mark Panning, project scientist for the InSight mission, during a NASA press conference, “we are able to really expand the family tree of understanding how these rocky planets form and how they’re similar and how they’re different.” 

Since InSight landed on Mars in 2018, its seismometer, which sits on the surface of the planet, has picked up more than a thousand distinct quakes. Most are so small they would be unnoticeable to someone standing on Mars’s surface. But a few were big enough to help the team get the first true glimpse of what’s happening underneath. 

NASA/JPL-CALTECH

Marsquakes create seismic waves that the seismometer detects. Researchers created a 3D map of Mars using data from two different kinds of seismic waves: shear and pressure waves. Shear waves, which can only pass through solids, are reflected off the planet’s surface.  

Pressure waves are faster and can pass through solids, liquids, and gases. Measuring the differences between the times that these waves arrived allowed the researchers to locate quakes and gave clues to the interior’s composition.  

One team, led by Simon Stähler, a seismologist at ETH Zurich, used data generated by 11 bigger quakes to study the planet’s core. From the way the seismic waves reflected off the core, they concluded it’s made from liquid nickel-iron, and that it’s far larger than had been previously estimated (between 2,230 and 2320 miles wide) and probably less dense. 

Another team, led by Amir Khan, a scientist at the Institute of Geophysics at ETH Zurich and at the Physics Institute at the University of Zurich, looked at the Martian mantle, the layer that sits between the crust and the core. They used the data to determine that Mars’s lithosphere—while similar in chemical composition to Earth’s—lacks tectonic plates. It is also thicker than Earth’s by about 56 miles.  

This extra thickness was most likely “the result of early magma ocean crystallization and solidification,” meaning that Mars may have been quickly frozen at a key point in its formative years, the team suggests. 

A third team, led by Brigitte Knapmeyer-Endrun, a planetary seismologist at the University of Cologne, analyzed the Martian crust, the layer of rocks at its surface. They found while its crust is likely very deep, it’s also thinner than her team expected.  

“That’s intriguing because it points to differences in the interior of the Earth and Mars, and maybe they are not made of exactly the same stuff, so they were not built from exactly the same building blocks,” says Knapmeyer-Endrun.  

The InSight mission will come to an end next year after its solar cells are unable to produce any more power, but in the meantime, it’s possible even more of Mars’s inner secrets will be unveiled.  

“Regarding seismology and InSight, there are also still many open questions for the extended mission,” says Knapmeyer-Endrun. 


We just got our best-ever look at the inside of Mars 2021/07/23 22:00

Is the UK’s pingdemic good or bad? Yes.

Oscar Maung-Haley, 24, was working a part-time job in a bar in Manchester, England, when his phone pinged. It was the UK’s NHS Test and Trace app letting him know he’d potentially been exposed to covid-19 and needed to self-isolate. The news immediately caused problems. “It was a mad dash around the venue to show my manager and say I had to go,” he says.

The alert he got was one of hundreds of thousands being sent out every week as the UK battles its latest wave of covid, which means more and more people face the same logistical, emotional, and financial challenges. An estimated one in five have resorted to deleting the app altogether—after all, you can’t get a notification if you don’t have it on your phone. The phenomenon is being dubbed a “pingdemic” on social media, blamed for everything from gas shortages to bare store shelves.

The ping deluge reflects the collision of several developments. The delta variant, which appears much easier to spread than others, has swept across the UK. At the same time, record numbers of Britons have downloaded the NHS app. Meanwhile, the UK has dropped many of its lockdown restrictions, so more people are coming into more frequent contact than before. More infections, more users, more contact: more pings. 

But that’s exactly how it’s supposed to work, says Imogen Parker, policy director for the Ada Lovelace Institute, which studies AI and data policies. In fact, even with so many notifications being sent, there are still many infections that the system is not catching. 

“More than 600,000 people have been told to isolate by the NHS covid-19 app across the week of July 8 in England and Wales,” she says, “but that’s only a little more than double the number of new positive cases in the same period. While we had concerns about the justification for the contact tracing app, criticizing it for the ‘pingdemic’ is misplaced: the app is essentially working as it always has been.”

Christophe Fraser, an epidemiologist at the University of Oxford’s Big Data Institute who has done the most prominent studies on the effectiveness of the app, says that while it is functioning as designed, there’s another problem: a significant breakdown in the social contract. “People can see, on TV, there are raves and nightclubs going on. Why am I being told to stay home? Which is a fair point, to be honest,” he says.

It’s this lack of clear, fair rules, he says, that is leading to widespread frustration as people are told to self-isolate. As we’ve seen throughout the pandemic, public health technology is deeply intertwined with everything around it—the way it’s marketed, the way it’s talked about in the media, the way it’s discussed by your physician, the way it’s supported (or not) by lawmakers. 

“People do want to do the right thing,” Fraser says. “They need to be met halfway.”

How we got here

Exposure notification apps are a digital public health tactic pioneered during the pandemic—and they’ve already weathered a lot of criticism from those who say that they didn’t get enough use. Dozens of countries built apps to alert users to covid exposure, sharing code and using a framework developed jointly by Google and Apple. But amid criticism over privacy worries and tech glitches, detractors charged that the apps had launched too late in the pandemic—at a time when case numbers were too high for tech to turn back the tide.

So shouldn’t this moment in the UK—when technical glitches have been ironed out, when adoption is high, and with a new wave spiking—be the right time for its app to make a real difference? 

“The science is not as much of a challenge … the challenge comes around the behavior. The hardest parts of the system are the parts where you need to convince people to do something.”

Jenny Wanger, Linux Foundation Public Health

Not if people don’t voluntarily follow the instructions to isolate, says Jenny Wanger, who leads covid-related tech initiatives for Linux Foundation Public Health. 

Eighteen months into the pandemic, “the tech is not usually a challenge,” she says. “The science is not as much of a challenge … we know, at this point, how covid transmission works. The challenge comes around the behavior. The hardest parts of the system are the parts where you need to convince people to do something—of course, based on best practices.”

Oxford’s Fraser says that he thinks about it in terms of incentives. For the average person, he says, the incentives for adhering to the rules of contact tracing—digital or otherwise—don’t always add up. 

If the result of using the app is that “you end up being quarantined but your neighbor who hasn’t installed the app doesn’t get quarantined,” he says, “that doesn’t necessarily feel fair, right?”

To make matters even more complicated, the UK has announced that it’s about to change its rules. In mid-August, people who have received two doses of a vaccine will no longer need to self-isolate because of covid exposure; they’ll only need to do so if they test positive. About half of the country’s adult population is fully vaccinated.

That could be a moment to bring incentives more in line with what people would be willing to do, he says. “Maybe people should be offered tests so that they can keep going to work and get on with life, rather than be isolated for a number of days.”

In the meantime, though, a handful of corporate leaders—the head of a budget airline, for example—have encouraged employees to delete the app to avoid the pings. Even the two most powerful politicians in the country, Prime Minister Boris Johnson and Chancellor Rishi Sunak, tried to skirt the requirement to isolate after being pinged (saying they were taking part in a trial of alternative measures) before public outcry forced them into quarantine.

When protection creates confusion

The mixed messages are compounded by the app’s privacy-protecting functions. Users aren’t told who among their contacts may have infected them—and they’re not told where any interactions happened. But that isn’t an accident: the apps were designed that way to safeguard people’s information.

“In epidemiology, surveillance is a noble thing,” says Fraser. “In digital tech, it’s a darker thing. I think the privacy-preserving protocol got the balance right. It’s incumbent on science and epidemiology to get information to people while preserving that privacy.”

Be that as it may, those privacy protections are now creating even more confusion.

Alistair Scott, 38, lives with his fiancée in North London. The couple did everything together during lockdown—yet Scott recently got a notification telling him he needed to isolate, while his partner did not. “It immediately became this game of ‘Why did I get pinged and you didn’t?’” he says. 

What’s next

Experts say that there are a few ways forward. One could be to tweak the algorithm: the app could incorporate new science about the length of covid exposure that might merit a ping even if you’re vaccinated. 

 “Emerging evidence looks like full vaccination should decrease the risk that someone transmits the virus by around half,” says Parker of the Ada Lovelace Institute. “That could have a sizeable impact on alerts if it was built into the model.” 

That means alerts could become less frequent for vaccinated people.

On the other hand, Wanger says that NHS leaders could adjust settings to be more sensitive, to reflect the increased transmission risk of variants like delta. There’s no indication that such changes have been made yet.

Either way, she says, what’s important is that the app keep doing its job.

“As a public health authority, when you’re looking at cases rising dramatically within your country, and you’re trying to pursue economic goals by lifting lockdown restrictions—it’s a really hard position to be in,” Wanger says. “You want to nudge people to do behavior changes, but you’ve got this whole psychology aspect to it. If people get notification fatigue, they are not going to change their behavior.”

Meanwhile, people are still being pinged, still feeling confused—and still hearing mixed messages.

Charlotte Wilson, 39, and her husband both downloaded the app onto their phones almost as soon as it was available. But there’s been a split in the household, especially since lawmakers were seen apparently trying to avoid the rules. Faced with the prospect of being told to self-isolate, Wilson said she would follow the advice, while her partner felt differently and deleted the app completely. 

“My husband thought [over the weekend], ‘You know what? This is ridiculous,’” she says. The impending change in self-isolation protocol made it seem especially fruitless.

Still, she understands his view, even if she’s personally keeping the app on her phone. 

“I don’t really know what the answer is as far as society’s concerned,” she says. “We’re just riddled with covid.”

This story is part of the Pandemic Technology Project, supported by The Rockefeller Foundation.


Is the UK’s pingdemic good or bad? Yes. 2021/07/23 10:00

DeepMind says it will release the structure of every protein known to science

Back in December 2020, DeepMind took the world of biology by surprise when it solved a 50-year grand challenge with AlphaFold, an AI tool that predicts the structure of proteins. Last week the London-based company published full details of that tool and released its source code.

Now the firm has announced that it has used its AI to predict the shapes of nearly every protein in the human body, as well as the shapes of hundreds of thousands of other proteins found in 20 of the most widely studied organisms, including yeast, fruit flies, and mice. The breakthrough could allow biologists from around the world to understand diseases better and develop new drugs. 

So far the trove consists of 350,000 newly predicted protein structures. DeepMind says it will predict and release the structures for more than 100 million more in the next few months—more or less all proteins known to science. 

“Protein folding is a problem I’ve had my eye on for more than 20 years,” says DeepMind cofounder and CEO Demis Hassabis. “It’s been a huge project for us. I would say this is the biggest thing we’ve done so far. And it’s the most exciting in a way, because it should have the biggest impact in the world outside of AI.”

Proteins are made of long ribbons of amino acids, which twist themselves up into complicated knots. Knowing the shape of a protein’s knot can reveal what that protein does, which is crucial for understanding how diseases work and developing new drugs—or identifying organisms that can help tackle pollution and climate change. Figuring out a protein’s shape takes weeks or months in the lab. AlphaFold can predict shapes to the nearest atom in a day or two.

The new database should make life even easier for biologists. AlphaFold might be available for researchers to use, but not everyone will want to run the software themselves. “It’s much easier to go and grab a structure from the database than it is running it on your own computer,” says David Baker of the Institute for Protein Design at the University of Washington, whose lab has built its own tool for predicting protein structure, called RoseTTAFold, based on AlphaFold’s approach.

In the last few months Baker’s team has been working with biologists who were previously stuck trying to figure out the shape of proteins they were studying. “There’s a lot of pretty cool biological research that’s been really sped up,” he says. A public database containing hundreds of thousands of ready-made protein shapes should be an even bigger accelerator.  

“It looks astonishingly impressive,” says Tom Ellis, a synthetic biologist at Imperial College London studying the yeast genome, who is excited to try the database. But he cautions that most of the predicted shapes have not yet been verified in the lab.  

Atomic precision

In the new version of AlphaFold, predictions come with a confidence score that the tool uses to flag how close it thinks each predicted shape is to the real thing. Using this measure, DeepMind found that AlphaFold predicted shapes for 36% of human proteins with an accuracy that is correct down to the level of individual atoms. This is good enough for drug development, says Hassabis.   

Previously, after decades of work, only 17% of the proteins in the human body have had their structures identified in the lab. If AlphaFold’s predictions are as accurate as DeepMind says, the tool has more than doubled this number in just a few weeks.

Even predictions that are not fully accurate at the atomic level are still useful. For more than half of the proteins in the human body, AlphaFold has predicted a shape that should be good enough for researchers to figure out the protein’s function. The rest of AlphaFold’s current predictions are either incorrect, or are for the third of proteins in the human body that don’t have a structure at all until they bind with others. “They’re floppy,” says Hassabis.

“The fact that it can be applied at this level of quality is an impressive thing,” says Mohammed AlQuraish, a systems biologist at Columbia University who has developed his own software for predicting protein structure. He also points out that having structures for most of the proteins in an organism will make it possible to study how these proteins work as a system, not just in isolation. “That’s what I think is most exciting,” he says.

DeepMind is releasing its tools and predictions for free and will not say if it has plans for making money from them in future. It is not ruling out the possibility, however. To set up and run the database, DeepMind is partnering with the European Molecular Biology Laboratory, an international research institution that already hosts a large database of protein information. 

For now, AlQuraishi can’t wait to see what researchers do with the new data. “It’s pretty spectacular,” he says “I don’t think any of us thought we would be here this quickly. It’s mind boggling.”


DeepMind says it will release the structure of every protein known to science 2021/07/22 17:00

An albino opossum proves CRISPR works for marsupials, too

Mice: check. Lizards: check. Squid: check. Marsupials … check.

CRISPR has been used to modify the genes of tomatoes, humans, and just about everything in between. Because of their unique reproductive biology and their relative rarity in laboratory settings, though, marsupials had eluded the CRISPR rush—until now.

A team of researchers at Japan’s Riken Institute, a national research facility, have used the technology to edit the genes of a South American species of opossum. The results were described in a new study out today in Current Biology. The ability to tweak marsupial genomes could help biologists learn more about the animals and use them to study immune responses, developmental biology, and even diseases like melanoma.

“I’m very excited to see this paper. It’s an accomplishment that I didn’t think would perhaps happen in my lifetime,” says John VandeBerg, a geneticist at the University of Texas Rio Grande Valley, who was not involved in the study.

The difficulties of genetically modifying marsupials had less to do with CRISPR than with the intricacies of marsupial reproductive biology, says Hiroshi Kiyonari (link in Japanese), the lead author of the new study.

While kangaroos and koalas are more well-known, researchers who study marsupials often use opossums in lab experiments, since they’re smaller and easier to care for. Gray short-tailed opossums, the species used in the study, are related to the white-faced North American opossums, but they’re smaller and don’t have a pouch.

The researchers at Riken used CRISPR to delete, or knock out, a gene that codes for pigment production. Targeting this gene meant that if the experiments worked, the results would be obvious at a glance: the opossums would be albino if both copies of the gene were knocked out, and mottled, or mosaic, if a single copy was deleted.

The resulting litter included one albino opossum and one mosaic opossum (pictured above). The researchers also bred the two, which resulted in a litter of fully albino opossums, showing that the coloring was an inherited genetic trait.

The researchers had to navigate a few hurdles to edit the opossum genome. First, they had to work out the timing of hormone injections to get the animals ready for pregnancy. The other challenge was that marsupial eggs develop a thick layer around them, called a mucoid shell, soon after fertilization. This makes it harder to inject the CRISPR treatment into the cells. In their first attempts, needles either would not penetrate the cells or would damage them so the embryos couldn’t survive, Kiyonari says.

The researchers realized that it would be a lot easier to do the injection at an earlier stage, before the coating around the egg got too tough. By changing when the lights turned off in the labs, researchers got the opossums to mate later in the evening so that the eggs would be ready to work with in the morning, about a day and a half later.

The researchers then used a tool called a piezoelectric drill, which uses electric charge to more easily penetrate the membrane. This helped them inject the cells without damaging them.

“I think it’s an incredible result,” says Richard Behringer, a geneticist at the University of Texas. “They’ve shown it can be done. Now it’s time to do the biology,” he adds. 

Opossums have been used as laboratory animals since the 1970s, and researchers have attempted to edit their genes for at least 25 years, says VandeBerg, who started trying to create the first laboratory opossum colony in 1978. They were also the first marsupial to have their genome fully sequenced, in 2007.

Comparative biologists hope the ability to genetically modify opossums will help them learn more about some of the unique aspects of marsupial biology that have yet to be decoded. “We find genes and marsupial genomes that we don’t have, so that creates a bit of a mystery as to what they’re doing,” says Rob Miller, an immunologist at the University of New Mexico, who uses opossums in his research.

Most vertebrates have two types of T cells, one of the components of the immune system (and lizards only have one type). But marsupials, including opossums, have a third type, and researchers aren’t sure what they do or how they work. Being able to remove the cells and see what happens, or knock out other parts of the immune system, might help them figure out what this mystery cell is doing, Miller says.

Opossums are also used as models for some human diseases. They’re among the few mammals that get melanoma (a skin cancer) like humans.

Another interesting characteristic of opossums is that they are born after only 14 days, as barely more than balls of cells with forearms to help them crawl onto their mother’s chest. These little jelly beans then develop their eyes, back limbs, and a decent chunk of their immune system after they’re already out in the world.

Since so much of their development happens after birth, studying and manipulating their growth could be much easier than doing similar work in other laboratory animals like mice. Kiyonari says his team is looking for other ways to tweak opossum genes to study the animals’ organ development. 

Miller and other researchers are hopeful that gene-edited opossums will help them make new discoveries about biology and about ourselves. “Sometimes comparative biology reveals what’s really important,” he says. “Things that we have in common must be fundamental, and things that are different are interesting.”


An albino opossum proves CRISPR works for marsupials, too 2021/07/21 17:00

Disability rights advocates are worried about discrimination in AI hiring tools

Your ability to land your next job could depend on how well you play one of the AI-powered games that companies like AstraZeneca and Postmates are increasingly using in the hiring process.

Some companies that create these games, like Pymetrics and Arctic Shores, claim that they limit bias in hiring. But AI hiring games can be especially difficult to navigate for job seekers with disabilities.

In the latest episode of MIT Technology Review’s podcast “In Machines We Trust,” we explore how AI-powered hiring games and other tools may exclude people with disabilities. And while many people in the US are looking to the federal commission responsible for employment discrimination to regulate these technologies, the agency has yet to act.

To get a closer look, we asked Henry Claypool, a disability policy analyst, to play one of Pymetrics’s games. Pymetrics measures nine skills, including attention, generosity, and risk tolerance, that CEO and cofounder Frida Polli says relate to job success.

When it works with a company looking to hire new people, Pymetrics first asks the company to identify people who are already succeeding at the job it’s trying to fill and has them play its games. Then, to identify the skills most specific to the successful employees, it compares their game data with data from a random sample of players.

When he signed on, the game prompted Claypool to choose between a modified version—designed for those with color blindness, ADHD, or dyslexia—and an unmodified version. This question poses a dilemma for applicants with disabilities, he says.

“The fear is that if I click one of these, I’ll disclose something that will disqualify me for the job, and if I don’t click on—say—dyslexia or whatever it is that makes it difficult for me to read letters and process that information quickly, then I’ll be at a disadvantage,” Claypool says. “I’m going to fail either way.”

Polli says Pymetrics does not tell employers which applicants requested in-game accommodations during the hiring process, which should help prevent employers from discriminating against people with certain disabilities. She added that in response to our reporting, the company will make this information more clear so applicants know that their need for an in-game accommodation is private and confidential.   

The Americans with Disabilities Act requires employers to provide reasonable accommodations to people with disabilities. And if a company’s hiring assessments exclude people with disabilities, then it must prove that those assessments are necessary to the job.

For employers, using games such as those produced by Arctic Shores may seem more objective. Unlike traditional psychometric testing, Arctic Shores’s algorithm evaluates candidates on the basis of their choices throughout the game. However, candidates often don’t know what the game is measuring or what to expect as they play. For applicants with disabilities, this makes it hard to know whether they should ask for an accommodation.

Safe Hammad, CTO and cofounder of Arctic Shores, says his team is focused on making its assessments accessible to as many people as possible. People with color blindness and hearing disabilities can use the company’s software without special accommodations, he says, but employers should not use such requests to screen out candidates.

The use of these tools can sometimes exclude people in ways that may not be obvious to a potential employer, though. Patti Sanchez is an employment specialist at the MacDonald Training Center in Florida who works with job seekers who are deaf or hard of hearing. About two years ago, one of her clients applied for a job at Amazon that required a video interview through HireVue.

Sanchez, who is also deaf, attempted to call and request assistance from the company, but couldn’t get through. Instead, she brought her client and a sign language interpreter to the hiring site and persuaded representatives there to interview him in person. Amazon hired her client, but Sanchez says issues like these are common when navigating automated systems. (Amazon did not respond to a request for comment.)

Making hiring technology accessible means ensuring both that a candidate can use the technology and that the skills it measures don’t unfairly exclude candidates with disabilities, says Alexandra Givens, the CEO of the Center for Democracy and Technology, an organization focused on civil rights in the digital age.

AI-powered hiring tools often fail to include people with disabilities when generating their training data, she says. Such people have long been excluded from the workforce, so algorithms modeled after a company’s previous hires won’t reflect their potential.

Even if the models could account for outliers, the way a disability presents itself varies widely from person to person. Two people with autism, for example, could have very different strengths and challenges.

“As we automate these systems, and employers push to what’s fastest and most efficient, they’re losing the chance for people to actually show their qualifications and their ability to do the job,” Givens says. “And that is a huge loss.”

A hands-off approach

Government regulators are finding it difficult to monitor AI hiring tools. In December 2020, 11 senators wrote a letter to the US Equal Employment Opportunity Commission expressing concerns about the use of hiring technologies after the covid-19 pandemic. The letter inquired about the agency’s authority to investigate whether these tools discriminate, particularly against those with disabilities.

The EEOC responded with a letter in January that was leaked to MIT Technology Review. In the letter, the commission indicated that it cannot investigate AI hiring tools without a specific claim of discrimination. The letter also outlined concerns about the industry’s hesitance to share data and said that variation between different companies’ software would prevent the EEOC from instituting any broad policies.

“I was surprised and disappointed when I saw the response,” says Roland Behm, a lawyer and advocate for people with behavioral health issues. “The whole tenor of that letter seemed to make the EEOC seem like more of a passive bystander rather than an enforcement agency.”

The agency typically starts an investigation once an individual files a claim of discrimination. With AI hiring technology, though, most candidates don’t know why they were rejected for the job. “I believe a reason that we haven’t seen more enforcement action or private litigation in this area is due to the fact that candidates don’t know that they’re being graded or assessed by a computer,” says Keith Sonderling, an EEOC commissioner.

Sonderling says he believes that artificial intelligence will improve the hiring process, and he hopes the agency will issue guidance for employers on how best to implement it. He says he welcomes oversight from Congress.

However, Aaron Rieke, managing director of Upturn, a nonprofit dedicated to civil rights and technology, expressed disappointment in the EEOC’s response: “I actually would hope that in the years ahead, the EEOC could be a little bit more aggressive and creative in thinking about how to use that authority.”

Pauline Kim, a law professor at Washington University in St. Louis, whose research focuses on algorithmic hiring tools, says the EEOC could be more proactive in gathering research and updating guidelines to help employers and AI companies comply with the law.

Behm adds that the EEOC could pursue other avenues of enforcement, including a commissioner’s charge, which allows commissioners to initiate an investigation into suspected discrimination instead of requiring an individual claim (Sonderling says he is considering making such a charge). He also suggests that the EEOC consult with advocacy groups to develop guidelines for AI companies hoping to better represent people with disabilities in their algorithmic models.

It’s unlikely that AI companies and employers are screening out people with disabilities on purpose, Behm says. But they “haven’t spent the time and effort necessary to understand the systems that are making what for many people are life-changing decisions: Am I going to be hired or not? Can I support my family or not?”


Disability rights advocates are worried about discrimination in AI hiring tools 2021/07/21 13:00

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