Month: August 2019

Amidst unrelenting chaos and violence, scientists and doctors in the Democratic Republic of Congo have been running a clinical trial of new drugs to try to combat a year-long Ebola outbreak. On Monday, the trial’s co-sponsors at the World Health Organization and the National Institutes of Health announced that two of the experimental treatments appear to dramatically boost survival rates.

While an experimental vaccine had previously been shown to shield people from catching Ebola, the announcement marks a first for people who have already been infected. “From now on, we will no longer say that Ebola is incurable,” said Jean-Jacques Muyembe, director general of the Institut National de Recherche Biomedicale, in the DRC, which has overseen the trial’s operations on the ground.

Starting last November, patients in four treatment centers in the country’s east, where the outbreak is at its worst, were randomly assigned to receive one of four investigational therapies—either an antiviral drug called remdesivir or one of three drugs that use monoclonal antibodies. Scientists concocted these big, Y-shaped proteins to recognize the specific shapes of invading bacteria and viruses and then recruit immune cells to attack those pathogens. One of these, a drug called ZMapp, is currently considered the standard of care during Ebola outbreaks. It had been tested and used during the devastating Ebola epidemic in West Africa in 2014, and the goal was to see if those other drugs could outperform it. But preliminary data from the first 681 patients (out of a planned 725) showed such strong results that the trial has now been stopped.

Patients receiving Zmapp in the four trial centers experienced an overall mortality rate of 49 percent, according to Anthony Fauci, director of the NIH’s National Institute of Allergy and Infectious Diseases. (Mortality rates are in excess of 75 percent for infected individuals who don’t seek any form of treatment.) The monoclonal antibody cocktail produced by a company called Regeneron Pharmaceuticals had the biggest impact on lowering death rates, down to 29 percent, while NIAID’s monoclonal antibody, called mAb114, had a mortality rate of 34 percent. The results were most striking for patients who received treatments soon after becoming sick, when their viral loads were still low—death rates dropped to 11 percent with mAb114 and just 6 percent with Regeneron’s drug, compared to 24 percent with ZMapp and 33 percent with Remdesivir.

Drugs based on monoclonal antibodies have become a mainstay of modern medicine—fending off diseases as disparate as cancer, arthritis, and lupus. But it takes many years of painstaking reverse-engineering to make them. Zmapp, for instance, was developed by infecting mice with Ebola and then collecting the antibodies the mice produced against the virus. Those antibodies then had to be further engineered to look more like a human antibody, so as not to provoke an immune reaction. Ebola infiltrates its victims’ cells using spiky proteins on the virus’s outer shell, so researchers screened the antibodies for the ones that did the best job of binding to those proteins. Block access, and the virus can’t replicate and spread. But compared to other viruses, Ebola is large and has the ability to change shape, making it difficult for any one antibody to block its infection. That’s why a cocktail approach has become favored, like the Regeneron product—a combination of three monoclonal antibodies generated first in mice.

An even better solution, some have posited, would be to mine the serum of Ebola survivors and harvest the DNA from the white blood cells that make antibodies. That would yield a set of genetic instructions for making antibodies with a proven track record against the Ebola virus. That’s what the NIH’s mAb114 is—an antibody isolated from the blood of a survivor of a 1995 outbreak in Kikwit, DRC. Scientists discovered it a few years ago—they had been circulating in his body for more than a decade.

With the WHO’s announcement a new trial will now kick off, directly comparing Regeneron to mAb114, which is being produced by a Florida-based company called Ridgeback Biotherapeutics. And all Ebola treatment units in the outbreak zone will now only administer the two most effective monoclonal antibody drugs, according to the WHO’s director of health emergencies, Mike Ryan.

“Today’s news puts us one more step to saving more lives,” said Ryan. “The success is clear. But there’s also a tragedy linked to the success. The tragedy is that not enough people are being treated. We are still seeing too many people staying away from treatment centers, people not being found in time to benefit from these therapies.”

Since the ongoing outbreak began last August in DRC’s North Kivu province, more than 2,800 people have become infected, with 1,794 confirmed deaths. It is the second-largest Ebola outbreak ever recorded. On July 17, the WHO declared it a “public health emergency of international concern,” after a case showed up in Goma, a large city bordering Rwanda. The risk of transmission across international borders remains high.

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Last winter, a hacker who goes by the handle Jmaxxz was looking for a Christmas present for his girlfriend. She’d recently flown back from a work trip and complained that her fingers had been painfully cold on her drive home from the airport, thanks to below-freezing winter weather and a circulatory system condition known as Raynaud’s disease. So Jmaxxz had the idea to buy her a remote starter that would connected to her car’s dashboard and, with an accompanying device and app called Linkr, allow her to start the car’s engine with a tap on her phone. That way, on her next trip, she could start heating up the car as soon as her plane touched down.

But even as he was installing that setup, he had misgivings. A security-minded software engineer for a company he declined to name, Jmaxxz wondered what sort of remote hacking he might have left his girlfriend’s car susceptible to. “In the back of my head I kept thinking, what’s the risk of this system, I’m putting her car on the internet,” he remembers. “I told myself, ‘ignorance is bliss. I’m not going to look at it. Don’t look at it.'”

He looked at it. And within 24 hours of doing so, in January of this year, he found exactly what he had feared: vulnerabilities that would let any hacker fully hijack that remote unlock and ignition device, providing a handy tool for stealing any of tens of thousands of vehicles. “You could locate cars, identify them, unlock them, start the car, trigger the alarm,” says Jmaxxz. “Really anything a legitimate user could do, you could do.”

In a talk at the Defcon hacker conference today in Las Vegas, Jmaxxz described a series of vulnerabilities in MyCar, a system made by Canadian company Automobility, whose software is rebranded and distributed under names including MyCar Kia, Visions MyCar, Carlink, and Linkr-LT1. MyCar’s devices and apps connect to radio-based remote start devices like Fortin, CodeAlarm, and Flashlogic, using GPS and a cellular connection to extend their range to anywhere with an internet connection. But with any of three different security flaws present across those apps—which Jmaxxz says he reported to the company and have since been fixed—he says he could have gained access to MyCar’s database backend, letting him or a less friendly hacker pinpoint and steal any car connected to the MyCar app, anywhere in the world.

Based on a scan of MyCar’s exposed database—and Jmaxxz says he was careful not to access anyone else’s private data—he estimates that there were roughly 60,000 cars left open to theft by those security bugs, with enough exposed data for a hacker to even choose the make and model of the car they wanted to steal. “You want a new Cadillac? You can find a new Cadillac,” Jmaxxz says.

When Jmaxxz began digging into the internals of Automobility’s apps in January, he says he first found that they included hardcoded administrator credentials, which he could pull out and use to access the company’s backend data. But even beyond that, he describes two other kinds of common hackable flaws—widespread SQL injection bugs and direct object references vulnerabilities—that would have let him gain access to the same data and send commands to other users’ vehicles.

Jmaxxz says he warned Automobility and the US Computer Emergency Response Team of those vulnerabilities in February of this year. They were fixed over the next months. But he says he continued to find and report lingering SQL injection vulnerabilities in MyCar’s code to MyCar’s developer Automobility, some of which weren’t fixed until just days before his Defcon talk. WIRED reached out to Automobility, who didn’t immediately respond. A notice on the CERT website in April confirmed the vulnerability, and includes a statement from Automobility. “All the resources at our disposal have been used to promptly address the situation, and we have fully resolved the issue,” the company wrote in the statement to CERT. “During this vulnerability period, no actual incident or issue with compromised privacy or functionality has been reported to us or detected by our systems.”

The danger of those bugs, Jmaxxz argues, went beyond theft or remote alarm-triggering pranks. Remotely starting a car without the owner’s knowledge could lead to dangerous carbon monoxide leaks, he points out. “If you start a car and it’s in a closed structure, you can end up in a situation where someone can die,” Jmaxxz says.

Separately, Jmaxxz says he found in his probing of MyCar’s database that it had also stored vastly more information about his girlfriend’s car than he expected. Over just 13 days, it had collected 2,000 locations of the car. “That one offends me more than all the others,” he says.”That’s not what I signed up for.”

Even now that Automobility has fixed the bugs that Jmaxxz reported, he argues that it still represents a worst-case scenario of internet-of-things companies that don’t carry out even basic security practices. “The problem is that these bugs shipped in the first place,” he says. “In my opinion this should have come up in any kind of security testing.”

Needless to say, Jmaxxz pulled the MyCar device out of his girlfriend’s car earlier this year. He eventually built his own DIY solution, with code he says he’ll make available on Github. The system, he says, will do just as good a job as MyCar at remotely warming up a car—and makes a better Christmas present than exposing her vehicle to an internet full of car thieves.

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Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. 

Related: The 12 Strangest Objects in the Universe

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

In July, a 17-year-old high school student in China was sticking protective film over 3,000 Amazon Echo dots a day at the Foxconn factory in Hengyang. She was working ten hours a day and six days a week. And she was among more than 1,000 students employed by the factory to work overtime on Amazon’s devices.

“I tried telling the manager of my line that I didn’t want to work overtime,” the student, who went by the pseudonym Xiao Fang, told anonymous researchers who leaked their findings and transcripts of interviews with workers to Chinese Labor Watch. “But the manager notified my teacher and the teacher said if I didn’t work overtime, I could not intern at Foxconn and that would affect my graduation and scholarship applications at the school. I had no choice, I could only endure this.”

The China Labor Watch report, published on Thursday, covers a 2019 investigation into the Foxconn Hengang factory and the Guardian was allowed to review the underlying documents. Among the report’s findings was the claim that high school students ages 16 through 18 across a number of schools were recruited to work at the factory, and teachers were tasked with pressuring the teens into working overtime or night shifts. That often meant physical and verbal attacks on these interns, the report states.

Like Xiao, some of these interns were reportedly assigned the job of making Echo and Echo dot devices as well as Kindles and were employed for over two months to help fill a labor gap at the factory.

Xiao Chen, 18, was another student that interned at the Foxconn factory, according to the report. In September of last year, his vocational school suspended classes so that all the students could intern at the factory, of which some reported this to the Hengyang Education Bureau. Xiao’s second time interning was voluntary—he works night shifts and manufactures Echo devices to help pay off student fees. He works ten hours a day, six days a week.

The China Labor Watch investigation found that Foxconn had recruited 1,581 interns from vocational schools as of July 26. The interns were paid about $1.42 per hour, which was a decreased wage from the previous year. They also didn’t get any living stipends or bonuses, which they had in 2018. Teachers received a $425 subsidy from the factory, and schools were given $0.42 for each hour an intern worked, so there was certainly an incentive for both the factory and the school to log more hours.

While it isn’t illegal for a 16-year-old to work in China, it does violate the country’s labor law for them to work overtime or night shifts. In notes from a meeting addressing the issue of potentially missing production goals without the students working on prohibited shifts, management made it clear that they were aware of the issue. The Guardian quotes a Foxxcon official telling attendees of the meeting that, “Nightshift line leaders should check in with student interns and teachers more often, and report back any abnormal situation so that teachers can persuade students to work nightshifts and overtime.”

This isn’t the first time Foxconn has been mired in controversy over its illegal labor practices regarding young workers. In 2017, six students ages 17 to 19 claimed that they had been working 11-hour days at a Foxconn plant in China as part of a mandatory, three-month program with their school. The students were reportedly among a group of 3,000 student interns tasked with helping to build the new iPhone X.

When reached for comment, an Amazon spokesperson told Gizmodo: 

We do not tolerate violations of our Supplier Code of Conduct. We regularly assess suppliers, using independent auditors as appropriate, to monitor continued compliance and improvement—if we find violations, we take appropriate steps, including requesting immediate corrective action. We are urgently investigating these allegations and addressing this with Foxconn at the most senior level. Additional teams of specialists arrived on-site this week to investigate, and we’ve initiated weekly audits of this issue.

A Foxconn spokesperson paraphrased by The Guardian said that the company “would increase the number of regular workers and review salaries immediately.”

Beyond just violating labor laws in China, the practice of exploiting students to meet the production needs during peak season is especially shitty when you remember just how much money Amazon is going to make off of their low-paid, intensely grueling, and academically valueless labor.