Slashdot Mirror

dryriver quotes Science Daily: Radiofrequency electromagnetic fields may have adverse effects on the development of memory performance of specific brain regions exposed during mobile phone use. These are the findings of a study involving nearly 700 adolescents in Switzerland. The investigation, led by the Swiss Tropical and Public Health Institute, will be published on Monday, 23 July 2018 in the peer-reviewed journal Environmental Health Perspectives. The study to be published found that cumulative RF-EMF brain exposure from mobile phone use over one year may have a negative effect on the development of figural memory performance in adolescents, confirming prior results published in 2015.

Figural memory is mainly located in the right brain hemisphere, and association with RF-EMF was more pronounced in adolescents using the mobile phone on the right side of the head. 'This may suggest that indeed RF-EMF absorbed by the brain is responsible for the observed associations.' said Martin Röösli, Head of Environmental Exposures and Health at Swiss TPH.

A team of researchers at Glasgow University have built a robot that uses machine learning to run and analyze its own chemical reaction. The system is able to figure out every reaction that's possible from a given set of starting materials. Ars Technica reports: Most of its parts are dispersed through a fume hood, which ensures safe ventilation of any products that somehow escape the system. The upper right is a collection of tanks containing starting materials and pumps that send them into one of six reaction chambers, which can be operated in parallel. The outcomes of these reactions can then be sent on for analysis. Pumps can feed samples into an IR spectrometer, a mass spectrometer, and a compact NMR machine -- the latter being the only bit of equipment that didn't fit in the fume hood. Collectively, these can create a fingerprint of the molecules that occupy a reaction chamber. By comparing this to the fingerprint of the starting materials, it's possible to determine whether a chemical reaction took place and infer some things about its products.

All of that is a substitute for a chemist's hands, but it doesn't replace the brains that evaluate potential reactions. That's where a machine-learning algorithm comes in. The system was given a set of 72 reactions with known products and used those to generate predictions of the outcomes of further reactions. From there, it started choosing reactions at random from the remaining list of options and determining whether they, too, produced products. By the time the algorithm had sampled 10 percent of the total possible reactions, it was able to predict the outcome of untested reactions with more than 80-percent accuracy. And, since the earlier reactions it tested were chosen at random, the system wasn't biased by human expectations of what reactions would or wouldn't work. The research has been published in the journal Nature.

Senators in Hawaii and South Dakota have introduced a bill, called the "Reliable Emergency Alert Distribution Improvement (READI) act, that would "explore" broadcasting alerts to "online streaming services, such as Netflix and Spotify," amongst other changes to the Emergency Alert System. TechCrunch reports: Some of the other things the bill touches on:
- Users on many phones can currently disable federal alerts; they want to get rid of that option
- Building a better system for reporting false alarms and figuring out what happened
- Updating the system to better prevent false alarms, and to better retract them when they do happen

Facebook has repeatedly referenced to lawmakers a "threshold" that must be reached before the platform decides to ban a particular page for violating the site's policies, but it hasn't discussed its guidelines publicly. Motherboard has obtained internal Facebook documents laying out what this threshold is for multiple types of different content, including some instances of hate speech. From the report: One Facebook moderator training document for hate speech says that for Pages -- Facebook's feature for sections dedicated to, say, a band, organization, public figure, or business -- the Page admin has to receive 5 "strikes" within 90 days for the Page itself to be deleted. Alternatively, Facebook moderators are told to remove a Page if at least 30 percent of the content posted by other people within 90 days violates Facebook's community standards. A similar 30 percent-or-over policy exists for Facebook Groups, according to the document.

In a similar vein, another hate speech document says that a profile should be taken down if there are 5 or more pieces of content from the user which indicate hate propaganda, photos of the user present with another identifiable leader, or other related violations. Although the documents obtained by Motherboard were created recently, Facebook's policies change regularly, so whether these exact parameters remain in force is unclear. Of course this still depends on moderators identifying and labeling posts as violating to reach that threshold. [...] Another document focused on sexual content says moderators should unpublish Pages and Groups under the basis of sexual solicitation if there are over 2 "elements," such as the Page description, title, photo, or pinned post, that include either explicit solicitation of nude imagery, or, if the page is more subtle, includes either a method of contact or a location. This slide again reiterates the over 30 percent and 5 admin posts rules found in the hate speech document.

An anonymous reader quotes a report from Gizmodo: Scientists' models show that sound waves seem to travel too quickly through the old, stable cores of continents, called "cratons," which extend deep into the mantle at depths around 120 to 150 kilometers (75 to 93 miles). Through observations, experiments, and modeling, one team figured that a potential way to explain the sound speed anomaly would be the presence of a lot of diamonds, a medium that allows for a faster speed of sound than other crystals. Perhaps the Earth is as much as 2 percent diamonds by volume, they found. Scientists have modeled the rock beneath continents through tomography, which you can think of as like an x-ray image, but using sound waves. But sound-wave velocities of around 4.7 kilometers per second (about 10,513 mph) are faster than sound-wave velocities in other kinds of minerals beneath the crust, according to the paper in the journal Geochemistry, Geophysics, Geosystems.

The researchers realized that if the regions had either 3 percent diamonds by volume or 50 percent of a rock formed at high pressure and temperature called eclogite, it would enable the sound speeds they observed. But both of those numbers seemed too high, based on observations of the minerals that end up on the Earth's surface: diamond-containing rocks called kimberlites. The researchers compromised and figured that 20 percent eclogite and 2 percent diamonds could explain the high velocities. The diamonds could be sprinkled as crystals found uniformly throughout the cratons.

Netflix shares plunged by more than 14% on Monday, after the firm reported disappointing subscriber growth. While the entertainment service added 5.2 million subscribers last quarter, it forecasted a growth of 6.2 million. BBC reports: Investors are worried about Netflix's growth potential in the face of increased competition from tech giants such as Apple, YouTube and Amazon, as well as traditional firms, which have started to invest more in online streaming. Disney, for example, plans to launch its own streaming service and stop licensing some of its material to Netflix.

In a letter to investors, Netflix called it a "strong but not stellar quarter," ending with about 130 million subscribers globally. The firm added just 670,000 subscribers in the U.S. -- far short of the more than one million it added in the second quarter of 2017. It added 4.5 million subscribers internationally, fewer than the two most recent quarters but up 8% year-on-year. However, it said its finances were strong. The company reported $3.9 billion in quarterly revenue, up 40% compared to the second quarter of 2017. Profits totaled $384.3 million, almost six times the figure during the same period a year ago.

Many booksellers on Amazon strive to sell their wares as cheaply as possible. That, after all, is usually how you make a sale in a competitive marketplace. Other merchants favor a counterintuitive approach: Mark the price up to the moon. From a report: "Zowie," the romance author Deborah Macgillivray wrote on Twitter last month after she discovered copies of her 2009 novel, "One Snowy Knight," being offered for four figures. One was going for "$2,630.52 & FREE Shipping," she noted. Since other copies of the paperback were being sold elsewhere on Amazon for as little as 99 cents, she was perplexed. "How many really sell at that price? Are they just hoping to snooker some poor soul?" Ms. Macgillivray wrote in an email. She noted that her blog had gotten an explosion in traffic from Russia. "Maybe Russian hackers do this in their spare time, making money on the side," she said.

Amazon is by far the largest marketplace for both new and used books the world has ever seen, and is also one of the most inscrutable. The retailer directly sells some books, while others are sold by third parties. The wild pricing happens with the latter. [...] Third-party sellers, Guru Hariharan, chief executive of Boomerang Commerce, said, come in all shapes and sizes -- from well-respected national brands that are trying to maintain some independence from Amazon to entrepreneurial individuals who use Amazon's marketplace as an arbitrage opportunity. These sellers list products they have access to, adjusting price and inventory to drive profits. Then there are the wild pricing specialists, who sell both new and secondhand copies.

"By making these books appear scarce, they are trying to justify the exorbitant price that they have set," said Mr. Hariharan, who led a team responsible for 15,000 online sellers when he worked at Amazon a decade ago. [...] A decade ago, Elisabeth Petry wrote a tribute to her mother, the renowned novelist Ann Petry. "At Home Inside," published by the University of Mississippi Press, is now out of print, but late last week secondhand copies were for sale on Amazon. A discarded library copy was $1,900. One seller offered two copies, each for $1,967, although only one was described as "Nice!" All these were a bargain compared with the copy that cost $2,464.

An anonymous reader quotes a report from the BBC: Best known for its Viking history, snow sports and jaw-dropping fjords, Norway is making a new name for itself as the only major economy in Europe where young people are getting markedly richer. People in their early thirties in Norway have an average annual disposable household income of around 460,000 kroner (around $56,200). Young Norwegians have enjoyed a 13% rise in disposable household income in real terms compared to Generation X (those born between 1966 and 1980) when they were the same age. These startling figures come from the largest comparative wealth data set in the world, the Luxembourg Income Database, and were analyzed in a recent report on generational incomes for the UK Think Tank The Resolution Foundation.

Compare this with young people in other strong economies: U.S. millennials have experienced a 5% dip, in Germany it's a 9% drop. For those living in southern Europe (the southern Eurozone suffered the brunt of the global economic crisis in 2008), disposable incomes have plunged by as much as 30%. Norway's youth unemployment rate (among 15- to 29-year-olds) is also relatively low at 9.4% compared to an OECD average of 13.9%. According to the BBC, this can be attributed to the country's rapid economic growth, thanks largely to their huge oil and gas sectors. "After seeing the biggest increase in average earnings of any large high-income economy between 1980 and 2013, it now leads multiple global rankings for wealth and wellbeing."

Thursday Elon Musk gave a surprisingly candid interview about Tesla's massive push to increase production of Model 3 sedans to 5,000 a week. An anonymous reader quotes Musk's remarks to Bloomberg: I spent almost the entire time in the factory the final week, and yeah, it was essentially three months with a tiny break of like one day that I wasn't there. I was wearing the same clothes for five days. Yeah, it was really intense. And everybody else was really intense, too... I think we had to prove that we could make 5,000 cars in a week -- 5,000 Model 3s and at the same time make 2,000 S and X's, so essentially show that we could make 7,000 cars. We had to prove ourselves. The number of people who thought we would actually make it is very tiny, like vanishingly small. There was suddenly the credibility of the company, my credibility, you know, the credibility of the whole team. It was like, "Can you actually do this or not?"

There were a lot of issues that we had to address in order to do it. You know, we had to create the new general assembly line in basically less than a month -- to create it and get to an excess of a 1,000-cars-a-week rate in like four weeks... A lot of the hoped-for automation was counterproductive. It's not like we knew it would be bad, because why would we buy a ticket to hell...? A whole bunch of the robots are turned off, and it was reverted to a manual station because the robots kept faulting out. When the robot faults out -- like the vision system can't figure out how to put the object in -- then you've got to reset the system. You've got to manually seat the components. It stops the whole production line while you sort out why the robot faults out.
When the interviewer asks why that happens, Musk replies, "Because we were huge idiots and didn't know what we were doing. That's why."

Sean Michael Kerner, writing for eSecurity Planet: Back in 1999, Eric Raymond coined the term "Linus' Law," which stipulates that given enough eyeballs, all bugs are shallow. Linus' Law, named in honor of Linux creator Linus Torvalds, has for nearly two decades been used by some as a doctrine to explain why open source software should have better security. In recent years, open source projects and code have experienced multiple security issues, but does that mean Linus' Law isn't valid?

According to Dirk Hohndel, VP and Chief Open Source Officer at VMware, Linus' Law still works, but there are larger software development issues that impact both open source as well as closed source code that are of equal or greater importance. "I think that in every development model, security is always a challenge," Hohndel said. Hohndel said developers are typically motivated by innovation and figuring out how to make something work, and security isn't always the priority that it should be. "I think security is not something we should think of as an open source versus closed source concept, but as an industry," Hohndel said.

We don't yet know if there's life on other worlds, however likely that is, but NASA's Kepler Mission satellite has helped pinpoint the abundance of planets orbiting other stars starting in May 2009. So far, it has provided data that scientists have used to confirm the existence of 2,650 exoplanets in a field of over 150,000 stars that it's examining. But that long service is about to end, as NASA said this week the craft is running out of fuel. From a report: The space agency has put the satellite into a form of hibernation until August 2, when there's time booked on the Deep Space Network -- a global array of receivers for space missions -- to download data from its 18th observational mission. Following that download, NASA will use the remaining fuel to start a 19th session. Fortunately, its successor is already in place and operational. The Transiting Exoplanet Survey Satellite (TESS) launched in April 2018, and produced a test image in May. TESS is a massive upgrade, observing almost 400 times the region of space as Kepler, or about 85% of what's observable from its orbit relative to Earth. Kepler is already a survivor, continuing to operate after part of the gyroscope mechanism failed that let it target star fields. Four wheels rotate in the gyroscope to provide a reaction that allows the necessarily precision in tracking, and two of the four failed by May 2013. NASA mission scientists figured out a clever workaround, in which they used pressure from the Sun to provide additional positioning assistance. The mission resumed under the moniker K2 in May 2014.

An anonymous reader quotes a report from the BBC: Professor Veena Sahajwalla's mine in Australia produces gold, silver and copper -- and there isn't a pick-axe in sight. Her "urban mine" at the University of New South Wales (UNSW) is extracting these materials not from rock, but from electronic gadgets. The Sydney-based expert in materials science reckons her operation will become efficient enough to be making a profit within a couple of years. "Economic modeling shows the cost of around $500,000 Australian dollars for a micro-factory pays off in two to three years, and can generate revenue and create jobs," she says. "That means there are environmental, social and economic benefits." In fact, research indicates that such facilities can actually be far more profitable than traditional mining.

According to a study published recently in the journal Environmental Science & Technology, a typical cathode-ray tube TV contains about 450g of copper and 227g of aluminum, as well as around 5.6g of gold. While a gold mine can generate five or six grammes of the metal per tonne of raw material, that figure rises to as much as 350g per tonne when the source is discarded electronics. The figures emerged in a joint study from Beijing's Tsinghua University and Macquarie University, in Sydney, where academics examined data from eight recycling companies in China to work out the cost for extracting these metals from electronic waste.

Amateur and professional musicians alike may spend hours poring over YouTube clips to figure out exactly how to play certain parts of their favorite songs. But what if there were a way to play a video and isolate the only instrument you wanted to hear? MIT News: That's the outcome of a new AI project out of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL): a deep-learning system that can look at a video of a musical performance, and isolate the sounds of specific instruments and make them louder or softer. The system, which is "self-supervised," doesn't require any human annotations on what the instruments are or what they sound like. Trained on over 60 hours of videos, the "PixelPlayer" system can view a never-before-seen musical performance, identify specific instruments at pixel level, and extract the sounds that are associated with those instruments. For example, it can take a video of a tuba and a trumpet playing the "Super Mario Brothers" theme song, and separate out the soundwaves associated with each instrument. The researchers say that the ability to change the volume of individual instruments means that in the future, systems like this could potentially help engineers improve the audio quality of old concert footage. You could even imagine producers taking specific instrument parts and previewing what they would sound like with other instruments (i.e. an electric guitar swapped in for an acoustic one).

An anonymous reader quotes a report from The Outline: As if they weren't already doing the absolute most, the die-hard fans of the rap group Insane Clown Posse have become accidental heroes for people concerned about facial recognition tech: According to Twitter user @tahkion, a computer science blogger for WonderHowTo, Juggalo makeup outmatches the machine learning algorithms that govern facial recognition technology.

In a series of follow-up tweets, @tahkion explained that facial recognition works by pinpointing the areas of contrast on a human face -- for instance, where a nose is located, or where the chin becomes the neck. As it happens, juggalo makeup often involves applying black paint below the mouth, but above the chin. That makes facial recognition vulnerable to misidentifying the placement of the jaw. Face-painting styles like "corpse" makeup also obscure the face. However, they don't create enough contrast to effectively confuse most facial recognition systems. Dramatic styles of feminine makeup, like heavy eyeliner, also are generally not enough to confuse facial recognition systems, @tahkion claims. However, facial recognition tech such as Apple's Face ID, which does not rely on visible light and uses depth perception, would not be tricked by juggalo makeup.

An anonymous reader quotes a report from Smithsonian: The science of longevity is surprisingly controversial, mainly because there are so few people of extreme old age -- defined at 110 years or older -- around to study. So researchers look to statistics to try and figure out how long people can live. [Ben Guarino reports via The Washington Post] that in 1825, actuary Benjamin Gompertz put forth the idea that the odds of dying grow exponentially as we age. Further research bears that out. Between the age of 30 and 80, the odds of dying double every 8 years. What happens after that, however, is not completely figured out. According to a controversial study released in 2016, which analyzed data from 40 different countries, the average person could make it to 115 with the right genes and interventions, and a few genetic superstars would be able to make it to 125. But that was it, they argued. There was a wall of mortality that medicine and positive thinking simply cannot overcome.

But not everyone is convinced by that data. That's why for the new paper in the journal Science, researchers looked at the lifespans of 3,836 people in Italy who reached the age of 105 or older between 2009 and 2015, with their ages verified by birth certificates. What they found is that the Gompertz law goes a little haywire around the century mark. According to a press release, a 90 year old woman has a 15 percent chance of dying in the next year, and an estimated six years left to live. At age 95, the chance of dying per year jumps to 24 percent. At the age of 105, the chance of dying makes another leap to 50 percent. But then, surprisingly, it levels off, even past 110. In other words, at least statistically, each year some lucky person could flip the coin of life, and if it comes up heads every time, they could live beyond 115 or 125.

An anonymous reader quotes a report from TechCrunch: A week after appointing a CEO for its healthcare joint venture with Berkshire Hathaway and JPMorgan, Amazon today announced an acquisition that underscores how it also hopes to have a more direct -- and more commercial -- role in the world of healthcare in the coming years. The company has purchased PillPack, an online pharmacy the lets users buy medications in pre-made doses. Terms of the deal have not been disclosed by Amazon, but sources close to the deal say it was for just under $1 billion.

PillPack has a license to operate in all 50 states in the U.S. and has other accreditations such as URAC AND VIPPS, but it doesn't seem to be operational in international markets. Its PharmacyOS -- the system it has built that forms the basis of the company -- is a platform that helps manage patient data and figure out how to balance meds together in safe doses for its customers.

Sample this: Me: So that's the marshmallow but you're going to eat it with this graham cracker and chocolate.
[My son looks at me like I am the dumbest person alive.]
Sebastian: No, I'm going to eat it with my MOUTH.
[End of play.] That's from "S'MORES. A Real-Life One-Act Play", a conversation between Hamilton impresario Lin-Manuel Miranda which his young son Sebastian. In that brief interaction, young Sebastian Miranda inadvertently hit upon a kind of ambiguity that reveals a great deal about how people learn and process language -- and how we might teach computers to do the same.

The misinterpretation on which the s'mores story hinges is hiding in the humble preposition with. Imagine the many ways one could finish this sentence: I'm going to eat this marshmallow with ... If you're in the mood for s'mores, then "graham cracker and chocolate" is an appropriate object of the preposition with. But if you want to split the marshmallow with a friend, you could say you're going to eat it "with my buddy Charlie." The Atlantic elaborates: Somehow speakers of English master these many possible uses of the word with without anyone specifically spelling it out for them. At least that's the case for native speakers -- in a class for English as a foreign language, the teacher likely would tease apart these nuances. But what if you wanted to provide the same linguistic education to a machine?

As it happens, just days after Miranda sent his tweet, computational linguists presented a conference paper exploring exactly why such ambiguous language is challenging for a computer-based system to figure out. The researchers did so using an online game that serves as a handy introduction to some intriguing work currently being done in the field of natural language processing (NLP). The game, called Madly Ambiguous , was developed by the linguist Michael White and his colleagues at Ohio State University. In it, you are given a challenge: to stump a bot named Mr. Computer Head by filling the blank in the sentence Jane ate spaghetti with ____________. Then the computer tries to determine which kind of with you intended. Playful images drive the point home. [Editor's note: check the article for corresponding images.]

In the sentence Jane ate spaghetti with a fork, Mr. Computer Head should be able to figure out that the fork is a utensil, and not something that is eaten in addition to the spaghetti. Likewise, if the sentence is Jane ate spaghetti with meatballs, it should be obvious that meatballs are part of the dish, not an instrument for eating spaghetti.

An anonymous reader shares a report: It looks cold, dark and empty, but astronomers have revealed that interstellar space is permeated with a fine mist of grease-like molecules. The study provides the most precise estimate yet of the amount of "space grease" in the Milky Way, by recreating the carbon-based compounds in the laboratory. The Australian-Turkish team discovered more than expected: 10 billion trillion trillion tonnes of gloop, or enough for 40 trillion trillion trillion packs of butter. Prof Tim Schmidt, a chemist at the University of New South Wales, Sydney and co-author of the study, said that the windscreen of a future spaceship travelling through interstellar space might be expected to get a sticky coating. "Amongst other stuff it'll run into is interstellar dust, which is partly grease, partly soot and partly silicates like sand," he said, adding that the grease is swept away within our own solar system by the solar wind. The findings bring scientists closer to figuring out the total amount of carbon in interstellar space, which fuels the formation of stars, planets and is essential for life.

dcblogs writes: LinkedIn has developed a new analytics platform that should make it easier to poach job candidates. It will use its vast database of nearly 600 million profiles to help recruiters find pockets of talent, know the attrition rate and glean competitive data. The platform, due in September, was discussed at a recent HR conference. One attendee asked a LinkedIn official: "Does that set up an environment for poaching talent?" And then she immediately answered her own question. "I think the answer is yes. And so why would I sign off on that?" In response to the attendees' question, Eric Owski, the head of product for Talent Insights at LinkedIn, said there was nothing wrong with making this data available. The LinkedIn team concluded that "the world is becoming more transparent," and "very sophisticated teams at large companies were able to figure out a lot of the calculations that we're making available in this product," he said. "We think by packaging it up nicely, it levels the playing field," Owski said. "We feel like we're on safe ground."

Last month IBM, which has staked much of its future on its flagship AI Watson, announced a major round of layoffs in the division. Now the engineers who had been let go allege that the move shows that difficulties IBM is facing in turning its AI into a profitable business. A report on IEEE Spectrum says: "IBM Watson has great AI," one engineer said, who asked to remain anonymous so he wouldn't lose his severance package. "It's like having great shoes, but not knowing how to walk -- they have to figure out how to use it." The layoffs at the end of May cut a swath through the Watson Health division. According to anonymous accounts submitted to the site Watching IBM, the cuts primarily affecting workers from three acquired companies: Phytel, Explorys, and Truven. These companies, acquired between 2015 and 2016, brought with them hefty troves of healthcare data, proprietary analytics systems to mine the data for insights, as well as their customers. The report adds: Two laid-off engineers from Phytel spoke to IEEE Spectrum in depth. They allege that IBM's leadership mismanaged their company since its acquisition, and say the problems at Phytel are emblematic of IBM's struggles to make Watson profitable. Several other Phytel employees corroborated the basic facts of their accounts. Both engineers worked for Phytel since before its 2015 acquisition, and say they were excited to become part of Big Blue. "Everyone expected that we would join IBM and be propelled by their support, that it would be the beginning of great things," says the first engineer.