Lunar Eclipse 2017 Guide: When, Where & How to See It - Wed, 08/02/2017 - 9:30am
The next lunar eclipse (a penumbral eclipse, in this case) will happen on Feb. 10, 2017. Here are the best places, times and tools to see it.
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Collapsing Beauty: Image of Antarctica's Larsen Ice Shelf - Wed, 08/02/2017 - 9:08am
A new satellite image shows the disappearing Larsen Ice Shelf of Antarctica.
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Mars 2020 Rover's Landing Site Will Undergo Hot Debate This Week - Wed, 08/02/2017 - 8:54am
Eight potential locations will be studied only three or four will be prioritized for exploration by NASA's next rover mission to the Red Planet.
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Saturn Could Be Defending Earth From Massive Asteroid Impacts - Wed, 08/02/2017 - 8:45am
Jupiter is often cited as Earth's protector — but Saturn may actually be hero of the day.
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Bill Nye's Back! Netflix's New Science Show Promises Nerdy Fun - Wed, 08/02/2017 - 8:40am
A trailer for the new Netflix talk show "Bill Nye Saves the World" promises loads of science experiments, celebrity guests and ultra-nerdy humor.
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Company to Launch Crewed 2017 Solar Eclipse Balloon Flight, High-Altitude Skydive - Wed, 08/02/2017 - 8:31am
A startup near-space ballooning company is hoping to not only capture spectacular footage of this August's solar eclipse over the United States, but also break the high-altitude jump record set by Felix Baumgartner in 2012.
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February Full Moon 2017: When to See the 'Snow Moon' Eclipse - Wed, 08/02/2017 - 8:30am
February's Snow Moon will be no ordinary full moon for skywatchers in most parts of the world, as it coincides with a special lunar eclipse that will cast a dusky shadow over the full moon's usual bright, glowing face.
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Massive Black Hole Appetite! Been Devouring Star For Decade | Video - Wed, 08/02/2017 - 7:24am
Astronomers using NASA's Chandra X-ray Observatory and Swift satellite, and the European Space Agency's XMM-Newton have been studying X-ray source XJ1500+154, which is 1.8 billion light-years from Earth.
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First Atomic Blast Reveals Clues About Moon Formation - Wed, 08/02/2017 - 7:01am
The explosion that opened the atomic age more than 70 years ago is helping scientists understand another dramatic event: the formation of the moon.
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Nuclear Fire-Formed Glass Used To Test Moon Formation Theory | Video - Wed, 08/02/2017 - 7:00am
A green-colored glass, called trinitite, was found 30 feet (10m) to 80 feet (250 m) away from ground zero after the first plutonium bomb test in 1945. They were lacking volatile elements similarly to that of lunar rocks.
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A Supermassive Black Hole Has Been Devouring a Star For a Decade

Slashdot - Wed, 08/02/2017 - 7:00am
An anonymous reader quotes a report from USA Today: A massive black hole devoured a star over a 10 year period, setting a new record for the longest space meal ever observed, according to new research. Researchers spotted the ravenous black hole with NASA's Chandra X-ray Observatory and Swift satellite as well as ESA's XMM-Newton, according to a statement from NASA. When objects like stars get too close to black holes, the intense gravity of the black hole can rip the star apart in what's called a tidal disruption event (TDE), according to NASA. While some of the debris from the star is flung forward, parts of it are pulled back and ingested by the black hole, where it heats up and emits an X-ray flare, NASA said in a statement. The tidal disruption event spotted by the trio of X-ray telescopes, is unlike anything researchers have ever seen, lasting ten times longer than any observed incident of star's death caused by a black hole, according to research published in Nature Astronomy Feb. 6. The black hole, dubbed XJ1500+0154, is located in a galaxy 1.8 billion light-years from Earth. Researchers first spotted it in 2005 and it reached peak brightness in 2008, according to the statement. According to NASA, researchers believe that the black hole may have consumed the most massive star ever completely torn apart during a TDE.

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Hidden Black Hole in Globular Cluster May Be a Cosmic Middle Child - Wed, 08/02/2017 - 6:55am
Astronomers studying a globular cluster have found a long-sought middleweight black hole in 47 Tucanae, a globular cluster, showing that such black holes could be hiding out in these compact groups of stars.
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New machine-learning algorithms may revolutionize drug discovery — and our understanding of life

Kurzweil AI - Wed, 08/02/2017 - 6:47am

A new set of machine-learning algorithms can generate 3D structures of complex nanoscale protein molecules like this complex proteasome map refined to 2.8 Angstroms (.28 nanometer) in 70 min with 49,954 particle images (credit: Structura Biotechnology Inc.)

A new set of machine-learning algorithms developed by researchers at the University of Toronto Scarborough can generate 3D structures of nanoscale protein molecules that could not be achieved in the past. The algorithms may revolutionize the development of new drug therapies for a range of diseases and may even lead to better understand how life works at the atomic level, the researchers say.

Drugs work by binding to a specific protein molecule and changing the protein’s 3D shape, which alters the way the drug works once inside the body. The ideal drug is designed in a shape that will only bind to a specific protein or group of proteins that are involved in a disease, while eliminating side effects that occur when drugs bind to other proteins in the body.

A significant computational problem

Since proteins are tiny — about 1 to 100 nanometers — even smaller than the shortest wavelength of visible light, they can’t be seen directly without using sophisticated techniques like electron cryomicroscopy (cryo-EM). Cryo-EM uses high-power microscopes to take tens of thousands of low-resolution images of a frozen protein sample from different positions.

The computational problem is to then piece together the correct high-resolution 3D structure from these 2D images.

Existing techniques take several days or even weeks to generate a 3D structure on a cluster of computers, requiring as much as 500,000 CPU hours, according to the researchers. Also, existing techniques often generate incorrect structures unless an expert user provides an accurate guess of the molecule being studied.

CryoSPARC machine learning algorithms can generate 3-D structures of nanoscale protein molecules (credit: Structura Biotechnology Inc)

New high-speed, deep-learning algorithms

That’s where the new set of algorithms* comes in. It reconstructs 3D structures of protein molecules using these images. “Our approach solves some of the major problems in terms of speed and number of structures you can determine,” says Professor David Fleet, chair of the Computer and Mathematical Sciences Department at U of Toronto Scarborough.

The algorithms could significantly aid in the development of new drugs because they provide a faster, more efficient means at arriving at the correct protein structure.

The new approach, called cryoSPARC, developed by the team’s startup, Structura Biotechnology Inc., eliminates the need for that prior knowledge and can make the computations possible in minutes on a single computer, using a standalone graphics processing unit (GPU) accelerated software package, according to the researchers.

The research was published in the current edition of the journal Nature Methods. It received funding from the Natural Sciences and Engineering Research Council of Canada (NSERC). The new cryo-EM platform is already being used in labs across North America, the researchers note.

* “We use an SGD [stochastic gradient descent] optimization scheme to quickly identify one or several low-resolution 3D structures that are consistent with a set of observed images. This algorithm allows for ab initio heterogeneous structure determination with no prior model of the molecule’s structure. Once approximate structures are determined, a branch-and-bound algorithm for image alignment helps rapidly refine structures to high resolution. The speed and robustness of these approaches allow structure determination in a matter of minutes or hours on a single inexpensive desktop workstation. … SGD was popularized as a key tool in deep learning for the optimization of nonconvex functions, and it results in near human-level performance in tasks like image and speech recognition.” — Ali Punjani et al./Nature Methods

University of Toronto Scarborough | New algorithms may revolutionize drug discoveries and our understanding of life

Abstract of cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination

Single-particle electron cryomicroscopy (cryo-EM) is a powerful method for determining the structures of biological macromolecules. With automated microscopes, cryo-EM data can often be obtained in a few days. However, processing cryo-EM image data to reveal heterogeneity in the protein structure and to refine 3D maps to high resolution frequently becomes a severe bottleneck, requiring expert intervention, prior structural knowledge, and weeks of calculations on expensive computer clusters. Here we show that stochastic gradient descent (SGD) and branch-and-bound maximum likelihood optimization algorithms permit the major steps in cryo-EM structure determination to be performed in hours or minutes on an inexpensive desktop computer. Furthermore, SGD with Bayesian marginalization allows ab initio 3D classification, enabling automated analysis and discovery of unexpected structures without bias from a reference map. These algorithms are combined in a user-friendly computer program named cryoSPARC

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Would the 'Hidden Figures' Leading Ladies Go to Space? | Video - Wed, 08/02/2017 - 6:44am
Actresses Taraj P. Henson (Katherine Jackson), Octavia Spencer (Dorothy Vaughan), and Janelle Monáe (Mary Jackson) give their answers to’s Sarah Lewin.
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The US Needs Real Data to Confront Bias in Police Shootings

Wired News - Wed, 08/02/2017 - 5:02am
Researchers learned police were twice as likely to fatally shoot unarmed black civilians. Those findings are terrible—and too hard to come by. The post The US Needs Real Data to Confront Bias in Police Shootings appeared first on WIRED.
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There Are Now Twice As Many Solar Jobs As Coal Jobs In the US

Slashdot - Wed, 08/02/2017 - 3:30am
According to a new survey from the nonprofit Solar Foundation, the solar industry now employs more than 260,000 people even though solar power provides just 1.3 percent of America's electricity. Last year, the industry accounted for one of every 50 new jobs nationwide. "Solar employs slightly more workers than natural gas, over twice as many as coal, over three times that of wind energy, and almost five times the number employed in nuclear energy," the report notes. "Only oil/petroleum has more employment (by 38%) than solar." Vox reports: This chart breaks it down by job type. The majority of solar jobs are in installation, with a median wage of $25.96 per hour. The residential market, which is the most labor-intensive, accounts for 41 percent of employment, the commercial market 28 percent, and the utility-scale market the rest. Now, mind you, comparing solar and coal is a bit unfair. Solar is growing fast from a tiny base, which means there's a lot of installation work to be done right now, whereas no one is building new coal plants in the U.S. anymore. (Quite the contrary: Many older coal plants have been closing in recent years, thanks to stricter air-pollution rules and cheap natural gas.) So solar is in a particularly labor-intensive phase at the moment. Still, it's worth thinking through what these numbers mean. One argument you could make about these numbers is that all this employment is, in a way, inefficient. If the solar industry hopes to keep pushing costs down and become a major U.S. energy source, it will likely need to become less labor-intensive over time. But labor costs are only one way to think about the issue. There's also a political angle here. America's energy system is inextricable from policy and politics, and an industry that creates a lot of jobs is inevitably going to have more influence over that process.

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A bridge of stars connects two dwarf galaxies

Science Daily - Wed, 08/02/2017 - 3:18am
The Magellanic Clouds, the two largest satellite galaxies of the Milky Way, appear to be connected by a bridge stretching across 43,000 light years, according to astronomers. The discovery is based on the galactic stellar census being conducted by the European Space Observatory, Gaia.
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Goldman Sachs Automated Trading Replaces 600 Traders With 200 Engineers

Slashdot - Wed, 08/02/2017 - 1:45am
Goldman Sach's New York headquarters has replaced 600 of its traders with 200 computer engineers over the last two decades or so, thanks to automated trading programs. (Though, the effort to do so has accelerated over the past five years.) "Marty Chavez, the company's deputy chief financial officer and former chief information officer, explained all this to attendees at a symposium on computer's impact on economic activity held by Harvard's Institute for Applied Computational Science last month," reports MIT Technology Review. From their report: The experience of its New York traders is just one early example of a transformation of Goldman Sachs, and increasingly other Wall Street firms, that began with the rise in computerized trading, but has accelerated over the past five years, moving into more fields of finance that humans once dominated. Chavez, who will become chief financial officer in April, says areas of trading like currencies and even parts of business lines like investment banking are moving in the same automated direction that equities have already traveled. Today, nearly 45 percent of trading is done electronically, according to Coalition, a U.K. firm that tracks the industry. In addition to back-office clerical workers, on Wall Street machines are replacing a lot of highly paid people, too. Complex trading algorithms, some with machine-learning capabilities, first replaced trades where the price of what's being sold was easy to determine on the market, including the stocks traded by Goldman's old 600. Now areas of trading like currencies and futures, which are not traded on a stock exchange like the New York Stock Exchange but rather have prices that fluctuate, are coming in for more automation as well. To execute these trades, algorithms are being designed to emulate as closely as possible what a human trader would do, explains Coalition's Shahani. Goldman Sachs has already begun to automate currency trading, and has found consistently that four traders can be replaced by one computer engineer, Chavez said at the Harvard conference. Some 9,000 people, about one-third of Goldman's staff, are computer engineers.

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Engineers develop powerful millimeter-wave signal generator

Science Daily - Wed, 08/02/2017 - 1:20am
Your doctor waves a hand-held scanner over your body and gets detailed, high-resolution images of your internal organs and tissues. Using the same device, the physician then sends gigabytes of data instantly to a remote server and just as rapidly receives information to make a diagnosis. Integrated circuit researchers have created a silicon microchip-based component that could make these and many other actions possible.
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Battlestar Galactica Actor Richard Hatch Dies At 71

Slashdot - Wed, 08/02/2017 - 1:15am
New submitter computerman413 writes: TMZ reports that Richard Hatch has passed away at 71 from pancreatic cancer. Hatch played Apollo on the original Battlestar Galactica, and had a recurring role as terrorist Tom Zarek on the reimagined Battlestar Galactica.

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