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Astrophysicists discover planets in extragalactic galaxies far away from milky way using microlensing

Astrophysicists discover planets in extragalactic galaxies far away from milky way using microlensing | Amazing Science | Scoop.it

A University of Oklahoma astrophysics team has discovered for the first time a population of planets beyond the Milky Way galaxy. Using microlensing—an astronomical phenomenon and the only known method capable of discovering planets at truly great distances from the Earth among other detection techniques—OU researchers were able to detect objects in extragalactic galaxies that range from the mass of the Moon to the mass of Jupiter.

 

Xinyu Dai, professor in the Homer L. Dodge Department of Physics and Astronomy, OU College of Arts and Sciences, with OU postdoctoral researcher Eduardo Guerras, made the discovery with data from the National Aeronautics and Space Administration's Chandra X-ray Observatory, a telescope in space that is controlled by the Smithsonian Astrophysical Observatory.

 

"We are very excited about this discovery. This is the first time anyone has discovered planets outside our galaxy," said Dai. "These small planets are the best candidate for the signature we observed in this study using the microlensing technique. We analyzed the high frequency of the signature by modeling the data to determine the mass."

 

While planets are often discovered within the Milky Way using microlensing, the gravitational effect of even small objects can create high magnification leading to a signature that can be modeled and explained in extragalactic galaxies. Until this study, there has been no evidence of planets in other galaxies.

 

"This is an example of how powerful the techniques of analysis of extragalactic microlensing can be. This galaxy is located 3.8 billion light years away, and there is not the slightest chance of observing these planets directly, not even with the best telescope one can imagine in a science fiction scenario," said Guerras. "However, we are able to study them, unveil their presence and even have an idea of their masses. This is very cool science."

 

For this study, OU researchers used the NASA Chandra X-ray Observatory at the Smithsonian Astrophysical Observatory. The microlensing models were calculated at the OU Supercomputing Center for Education and Research.

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Creating attraction between molecules deep inside the periodic table

Creating attraction between molecules deep inside the periodic table | Amazing Science | Scoop.it

A team of scientists provides the first experimental and theoretical proof that it is possible to form strong, stable attractions between some of the heavier elements in the periodic table—such as arsenic or even antimony. Because hydrogen is not involved in creating the bond between these elements, these new materials should be resistant to water and humidity.

Imagine a waterproof computer. It's not going to happen tomorrow, but it may no longer be a pipedream since a McGill-led international research team has shown for the first time that it is possible to form strong, stable attractions between some of the heavier elements in the periodic table. A recent article in Nature Communications provides the first experimental and theoretical proof that heavy, large atoms of an increasingly metallic nature—such as arsenic or even antimony—can be used to create new materials called cocrystals by using halogen bonds. Because hydrogen is not involved in creating the bond between these elements, these new materials should be resistant to water and humidity.

Creating co-crystals from deep in the periodic table

Much of recent research in chemistry has focused on creating new materials by manipulating the way that molecules recognize one another and come together to build more complex, self-organized structures. For example, cocrystals based on either hydrogen or halogen bonds have been extensively used by scientists in the design and manufacture of new improved pharmaceuticals, polymers with enhanced properties such as Kevlar, and more recently, materials for use in electronics. Until recently, such interactions invariably had to include at least one atom of a 'lighter' element found at the very top of the periodic table, such as hydrogen, nitrogen, oxygen, fluorine etc.

"Quite apart from the potentially practical applications of this discovery, it is a big advance in fundamental chemistry," says McGill chemistry Professor Tomislav Frišči?, one of the senior authors on the paper. "For the first time researchers have demonstrated molecular recognition events including only heavier elements located in the 4th and 5th periods. This is significantly deeper in the periodic table than has been seen until now. It is a very exciting time to be a chemist—it's as though we were explorers moving closer to the South Pole of the periodic table—and who knows what we will find there."

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Greenland's ice melting faster than scientists previously thought

Greenland's ice melting faster than scientists previously thought | Amazing Science | Scoop.it

The pace of ice loss has increased four-fold since 2003 as enormous glaciers are depositing ever larger chunks of ice into the Atlantic ocean, where it melts, causing sea levels to rise.

 

Enormous glaciers in Greenland are depositing ever larger chunks of ice into the Atlantic Ocean, where it melts. But scientists have found that the largest ice loss in the decade from 2003 actually occurred in the south-west region of the island, which is largely glacier-free.

 

This suggests surface ice is simply melting as global temperatures rise, causing gushing rivers of meltwater to flow into the ocean and push up sea levels. South-west Greenland, not previously thought of as a source of woe for coastal cities, is set to “become a major future contributor to sea level rise”, the research states.

 

“We knew we had one big problem with increasing rates of ice discharge by some large outlet glaciers,” said Michael Bevis, lead author of the paper and a professor of geodynamics at Ohio State University. “But now we recognize a second serious problem: increasingly, large amounts of ice mass are going to leave as meltwater, as rivers that flow into the sea.”

 

The research provides fresh evidence of the dangers posed to vulnerable coastal places as diverse as Miami, Shanghai, Bangladesh and various Pacific islands as climate change shrinks the world’s land-based ice. “The only thing we can do is adapt and mitigate further global warming – it’s too late for there to be no effect,” Bevis said. “This is going to cause additional sea level rise. We are watching the ice sheet hit a tipping point. “We’re going to see faster and faster sea level rise for the foreseeable future. Once you hit that tipping point, the only question is: how severe does it get?”

 

The study, published in Proceedings of the National Academy of Sciences, used data from Nasa’s gravity recovery and climate experiment (known as Grace) and GPS stations scattered across Greenland to analyze changes in ice mass.

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Radio jets from the Milky Way’s black hole could be pointing right at Earth

By blocking out scattered light, astronomers were able to study our central black hole's powerful radio jet — which might be looking right at us.

 

Using an array of 13 radio telescopes, astronomers from the Max Planck Institute were able to home in on Sagittarius A* (pronounced A-star), the region that houses the Milky Way’s supermassive black hole. And once they’d cleared out the noise of scattered light that surrounds it, they found that the powerful radio emission that blasts from the black hole is coming from just a tiny area, which could be aimed right at Earth. The research was published Monday in The Astrophysical Journal and, if confirmed, could shed new light on Sgr A* and its radio jets.

 

Supermassive black holes are pretty common in our universe, sitting at the hearts of most large galaxies. Their strong gravitational fields allow them to suck in and obliterate objects that get too close to them. And while they absorb most of this celestial matter, a small fraction escapes the black hole and blasts back out into space. These emissions, known as jets, emit radio waves and travel at nearly the speed of light.

And even though we can detect some of Sgr A*’s radio emissions from Earth, studying it is easier said than done. There's a cloud of hot gas that sits between Earth and Sgr A*. And this interstellar gas scatters the jets’ light, making it hard to clearly pinpoint radio waves from the black hole.

 

But recently, a team of researchers were able to isolate this radio emission using very long baseline interferometry — a technique that combines multiple telescopes to create a massive, extremely powerful one. Using 13 radio telescopes from around the world, they removed the effects of the hot gas to get a sharper image of the jets’ emission than ever before.

They found that it’s coming from a symmetrical source, which lines up well with the “jet” theory, since they blast from black holes in opposite directions. They also discovered that the emission is much narrower than they thought. So narrow, in fact, that it’s coming at us from just one 300 millionth of a degree — suggesting that it’s aimed almost directly at Earth.

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Carbon capture system turns CO2 into electricity and hydrogen fuel

Carbon capture system turns CO2 into electricity and hydrogen fuel | Amazing Science | Scoop.it
Inspired by the ocean’s role as a natural carbon sink, researchers at Ulsan National Institute of Science and Technology (UNIST) and Georgia Tech have developed a new system that absorbs CO2 and produces electricity and useable hydrogen fuel.

 

If we are going to reach the goal of keeping Earth from warming more than 1.5° C (2.7° F) this century, it's not enough to just reduce our carbon dioxide emissions – we need to actively clean it out of the atmosphere too. Inspired by the ocean's role as a natural carbon sink, researchers at Ulsan National Institute of Science and Technology (UNIST) and Georgia Tech have developed a new system that absorbs CO2 and produces electricity and useable hydrogen fuel.

 

The new device, which the team calls a Hybrid Na-CO2 System, is basically a big liquid battery. A sodium metal anode is placed in an organic electrolyte, while the cathode is contained in an aqueous solution. The two liquids are separated by a sodium Super Ionic Conductor (NASICON) membrane.

 
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China sprouts cotton plants on the moon

China sprouts cotton plants on the moon | Amazing Science | Scoop.it

In a scientific first for humankind, plants are growing on the surface of the moon, the South China Morning Post reports. Cotton, rapeseed, and potato seedlings have all sprouted inside a canister aboard China’s Chang’e-4 lunar lander, now parked on the far side of the moon. Yeast, fruit flies, and rock cress were also sent aboard Chang’e-4 as part of an experiment to investigate growth in low-gravity environments. The mission’s architects say the experiments could help lay a foundation for one day establishing a lunar base.

 

Professor Liu Hanlong, head of the experiment, announced on Tuesday that the cotton seeds were the first to sprout, but the team did not give an exact time for that event. Liu said that in addition to cotton, rapeseed and potato seeds had sprouted and were growing well as of Saturday.

 

Professor Xie Gengxin, the experiment’s chief designer, revealed that cotton, rapeseed, potato, arabidopsis – commonly known as rock cress – yeast and fruit flies were the six organisms chosen to go to the moon. “We have given consideration to future survival in space. Learning about these plants’ growth in a low-gravity environment would allow us to lay the foundation for our future establishment of space base,” Liu said. The container was equipped with a small but powerful control system to keep the interior at around 25 degrees Celsius (77 degrees Fahrenheit).

 

Liu reports that the six components behaved as “producers, consumers and decomposers” in the micro-ecosystem that arrived on the moon. The plants produced oxygen and food by photosynthesis and sustained the fruit flies. The canister was fully concealed from the extremes of temperature and strong radiation on the moon. Chinese scientists designed tubes for the canister to take natural Earth light to the moon for the plants to aid photosynthesis.

 

The yeast, acting as a decomposition agent, processed waste from the flies and the dead plants to create an additional food source for the insects. Liu explained that potatoes could be a main source food for space explorers, cotton could be used for clothing, and rapeseed could be a source of oil. Xie said the six species were chosen because they were small and could grow in a confined environment. They were also hardy enough to withstand some of the extreme conditions on the lunar surface.

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New Caledonian crows infer the weight of objects from observing their movements in a breeze

New Caledonian crows infer the weight of objects from observing their movements in a breeze | Amazing Science | Scoop.it

Humans use a variety of cues to infer an object's weight, including how easily objects can be moved. For example, if we observe an object being blown down the street by the wind, we can infer that it is light. A team of scientists tested now whether New Caledonian crows make this type of inference. After training that only one type of object (either light or heavy) was rewarded when dropped into a food dispenser, birds observed pairs of novel objects (one light and one heavy) suspended from strings in front of an electric fan. The fan was either on—creating a breeze which buffeted the light, but not the heavy, object—or off, leaving both objects stationary. In subsequent test trials, birds could drop one, or both, of the novel objects into the food dispenser. Despite having no opportunity to handle these objects prior to testing, birds touched the correct object (light or heavy) first in 73% of experimental trials, and were at chance in control trials. These results suggest that birds used pre-existing knowledge about the behavior exhibited by differently weighted objects in the wind to infer their weight, using this information to guide their choices.

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Google Brain Is Morphing Into A Translator for Artificial Intelligence

Google Brain Is Morphing Into A Translator for Artificial Intelligence | Amazing Science | Scoop.it
Neural networks are famously incomprehensible, so Been Kim is developing a “translator for humans.”

 

If a doctor told that you needed surgery, you would want to know why — and you’d expect the explanation to make sense to you, even if you’d never gone to medical school. Been Kim, a research scientist at Google Brain, believes that we should expect nothing less from artificial intelligence. As a specialist in “interpretable” machine learning, she wants to build AI software that can explain itself to anyone.

 

Since its ascendance roughly a decade ago, the neural-network technology behind artificial intelligence has transformed everything from email to drug discovery with its increasingly powerful ability to learn from and identify patterns in data. But that power has come with an uncanny caveat: The very complexity that lets modern deep-learning networks successfully teach themselves how to drive cars and spot insurance fraud also makes their inner workings nearly impossible to make sense of, even by AI experts. If a neural network is trained to identify patients at risk for conditions like liver cancer and schizophrenia — as a system called “Deep Patient” was in 2015, at Mount Sinai Hospital in New York — there’s no way to discern exactly which features in the data the network is paying attention to. That “knowledge” is smeared across many layers of artificial neurons, each with hundreds or thousands of connections.

 

As ever more industries attempt to automate or enhance their decision-making with AI, this so-called black box problem seems less like a technological quirk than a fundamental flaw. DARPA’s “XAI” project (for “explainable AI”) is actively researching the problem, and interpretability has moved from the fringes of machine-learning research to its center. “AI is in this critical moment where humankind is trying to decide whether this technology is good for us or not,” Kim says. “If we don’t solve this problem of interpretability, I don’t think we’re going to move forward with this technology. We might just drop it.”

 

Kim and her colleagues at Google Brain recently developed a system called “Testing with Concept Activation Vectors” (TCAV), which she describes as a “translator for humans” that allows a user to ask a black box AI how much a specific, high-level concept has played into its reasoning. For example, if a machine-learning system has been trained to identify zebras in images, a person could use TCAV to determine how much weight the system gives to the concept of “stripes” when making a decision.

 

TCAV was originally tested on machine-learning models trained to recognize images, but it also works with models trained on text and certain kinds of data visualizations, like EEG waveforms. “It’s generic and simple — you can plug it into many different models,” Kim says.

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Quantum brain computer: Scientists are planning to create a quantum computer that acts like a brain

Quantum brain computer: Scientists are planning to create a quantum computer that acts like a brain | Amazing Science | Scoop.it
Combining quantum computing with neural networks could produce AI that can make very complex decisions quickly.

 

The human brain has amazing capabilities making it in many ways more powerful than the world’s most advanced computers. So it’s not surprising that engineers have long been trying to copy it. Nowadays, artificial neural networks inspired by the structure of the brain are used to tackle some of the most difficult problems in artificial intelligence (AI). But this approach typically involves building software so information is processed in a similar way to the brain, rather than creating hardware that mimics neurons.

 

Scientists now hope to build the first dedicated neural network computer, using the latest “quantum” technology rather than AI software. By combining these two branches of computing, they hope to produce a breakthrough which leads to AI that operates at unprecedented speed, automatically making very complex decisions in a very short time. However, they need much more advanced AI if they want to create things like truly autonomous self-driving cars and systems for accurately managing the traffic flow of an entire city in real-time. Many attempts to build this kind of software involve writing code that mimics the way neurons in the human brain work and combining many of these artificial neurons into a network. Each neuron mimics a decision-making process by taking a number of input signals and processing them to give an output corresponding to either “yes” or “no”. Each input is weighted according to how important it is to the decision. For example, for AI that could tell you which restaurant you would most enjoy going to, the quality of the food may be more important than the location of the table that’s available, so would be given more weight in the decision-making process. These weights are adjusted in test runs to improve the performance of the network, effectively training the system to work better.

 

This was how Google’s AlphaGo software learned the complex strategy game Go, playing against a copy of itself until it was ready to beat the human world champion by four games to one. But the performance of the AI software strongly depends on how much input data it can be trained on (in the case of AlphaGo, it was how often it played against itself).

 

The new neuromorphic project aims to radically speed up this process and boost the amount of input data that can be processed by building neural networks that work on the principles of quantum mechanics. These networks will not be coded in software, but directly built in hardware made of superconducting electrical circuits. We expect that this will make it easier to scale them up without errors. Traditional computers store data in units known as bits, which can take one of two states, either 0 or 1. Quantum computers store data in “qubits”, which can take on many different states. Every extra qubit added to the system doubles its computing power. This means that quantum computers can process huge amounts of data in parallel (at the same time).

 

So far, only small quantum computers that demonstrate parts of the technology have been successfully built. Motivated by the prospect of significantly greater processing power, many universitiestech giants and start-up companies are now working on designs. But none have yet reached a stage where they can outperform existing (non-quantum) computers.

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We're one step closer to deciphering rodent languages

We're one step closer to deciphering rodent languages | Amazing Science | Scoop.it
UW researchers developed a software called DeepSqueak—derived from self-driving car technology—to demystify mouse and rat communication and monitor how our furry analogs fare in the lab.

 

Rodents like mice and rats have been staple creatures for laboratory research for nearly a century for good reasons: As human proxies for study, they share more than 97 percent of their DNA with our species. They also live shorter lives, have more babies, are cheaper to purchase and maintain and don’t need to sign waivers to give their lives to science. No wonder nearly 85 percent of the 25-million-plus lab animals used today are either rats or mice.

 

But despite their omnipresence in lab settings, rodent culture itself is still relatively understudied — especially the combination of chirping, bruxing and other behaviors that constitute rodent language. But a new software called DeepSqueak, outlined in Neuropsychopharmacology and developed by researchers at the University of Washington, could help demystify rodent language to better monitor how our furry analogs fare during experiments.

 

Nearly 40 years ago, researchers realized that rats and mice use language in the form of ultrasonic vocalizations (USVs) that we would need specialized equipment to hear. “What they do is they whistle, and when you slow it down 10 or 20 times, it sounds just like a bird call,” says Kevin Coffey, a postdoctoral researcher in the Psychiatry and Behavioral Science department at the University of Washington School of Medicine. Coffey has researched rodents (and owned them as pets) for more than a decade, giving him ample time to observe their habits. Researchers like himself have discovered that rodents make these 20 or so types of whistles — which scientists call syllables — depending on the scenario and what they want to accomplish, and structure them together in lots of different combinations, much like language.

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Astronomers Clock a Black Hole Spinning at Half the Speed of Light

Astronomers Clock a Black Hole Spinning at Half the Speed of Light | Amazing Science | Scoop.it
Researchers have used X-rays to calculated how fast a black hole spins, something that might help them see what happens as black holes age.

 

Black holes are massive beasts that annihilate anything that dares to cross them. We don’t know a whole lot about these invisible, terrifying bodies, but astronomers have found a new way to study their mysterious behavior.

 

By observing the X-rays blasting from a star torn apart by a black hole, a team of researchers were able to calculate how fast the black hole spins — clocking it at nearly 50 percent the speed of light. This marks the first time that astronomers used X-rays, which orbit the black hole every 131 seconds, to calculate its incredible speed. The research, which could help correlate a black hole’s age with its speed, was published today in the journal Science.

 

The discovery dates back to November 2014, when astronomers were observing a galaxy 300 million light years from Earth. They saw the galaxy’s central, supermassive black hole lure in and rip apart a passing star. Known as a tidal disruption flare, this event created a blast of X-ray radiation that was strong enough to be seen from Earth. Since black holes don’t emit many X-rays on their own, a group of researchers decided to home in on the event.

 

And luckily for them, various space telescopes started measuring the black hole’s X-ray emissions after the flare was spotted. After combing through their data, the MIT-led team noticed a peculiar trend. They found that bursts of X-rays were appearing once every 131 seconds near the black hole’s event horizon — the point where it starts to swallow up material. These periodic emissions, which persisted for over 450 days, boosted the black hole’s total X-rays emissions by 40 percent.

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Mysterious radio signals from deep space detected

Mysterious radio signals from deep space detected | Amazing Science | Scoop.it

Astronomers have revealed details of mysterious signals emanating from a distant galaxy, picked up by a telescope in Canada. The precise nature and origin of the blasts of radio waves is unknown.

 

Among the 13 fast radio bursts, known as FRBs, was a very unusual repeating signal, coming from the same source about 1.5 billion light years away. Such an event has only been reported once before, by a different telescope. "Knowing that there is another suggests that there could be more out there," said Ingrid Stairs, an astrophysicist from the University of British Columbia (UBC). "And with more repeaters and more sources available for study, we may be able to understand these cosmic puzzles - where they're from and what causes them."

 

The CHIME observatory, located in British Columbia's Okanagan Valley, consists of four 100-meter-long, semi-cylindrical antennas, which scan the entire northern sky each day. The telescope only got up and running last year, detecting 13 of the radio bursts almost immediately, including the repeater. The research has now been published in the journal Nature.

 

"We have discovered a second repeater and its properties are very similar to the first repeater," said Shriharsh Tendulkar of McGill University, Canada. "This tells us more about the properties of repeaters as a population." FRBs are short, bright flashes of radio waves, which appear to be coming from almost halfway across the Universe.

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Automatic Speaker Recognition using Transfer Learning AI

Automatic Speaker Recognition using Transfer Learning AI | Amazing Science | Scoop.it

Even with today’s frequent technological breakthroughs in speech-interactive devices (e.g., Siri and Alexa), few companies have tried enabling multi-user profiles. Google Home has been the most ambitious in this area, allowing up to six user profiles. The recent boom of this technology is what made the potential for this project very exciting to a team of computer engineers. They also wanted to engage in a project that is a hot topic in deep-learning research, create interesting tools, learn more about neural network architectures, and make original contributions where possible.

The computer scientists sought to create a system able to quickly add user profiles and accurately identify their voices with very little training data, a few sentences as most! This learning from one to only a few samples is known as One Shot Learning. This article will outline the different phases of the project in detail.


Via Eric Feuilleaubois
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Jumping genes made us human, but can they also cause disease?

Jumping genes made us human, but can they also cause disease? | Amazing Science | Scoop.it

Genes can jump when bacteria or viruses infect humans. Although our cells have mechanisms to counteract such events, some mobile DNA fragments become established in our cells, where they add genetic diversity.

 

The first jumping genes in our evolution can be traced back as far as 600 million years ago, to the human ancestor Giardi lamblia, a primitive parasite. Once mammals arrived on the scene, insertions of mobile DNA into their genomes really took off. This happened between 40 and 12 million years ago. Exactly how these ancient jumping genes contributed to the development of the modern human is unclear. Scientists think that their step-wise integration coincided with the emergence of an increasingly complex brain structure, possibly giving us a crucial advantage during primate evolution. And their influence can still be felt today.

 

Today, we know that jumping genes are important for placental development and actively regulate gene expression during early embryonic development. The jumping gene known as HERVK is thought to be a remnant of an infection by an ancient retrovirus that took up residence in the genome around 200,000 years ago. HERVK is switched on at the very early stage of human embryonic development and triggers a precise antiviral response, even though no virus is present. Scientists think that this event may provide the developing embryo with some level of viral resistance, which is, of course, a favorable trait.

 

Jumping genes are also known to play crucial roles in brain function. One such gene contains a regulatory RNA molecule that is important for normal human brain development. If this is mutated, it causes infantile encephalopathy. While we now know that jumping genes contribute to normal body functions, they also have the potential to wreak serious havoc with our genes.

 

Jumping genes and disease

Mobile DNA can jump to another location on the same chromosome or a different chromosome each time a cell divides. If this happens in sperm or egg cells, it will be passed on to the next generation. The current estimate of such events occurring ranges from 1 in 20 to 1 in 1,000 births. These jumps can disrupt normal gene function and result in spontaneous emergence of heritable diseases, such as blood disorders, neurodegeneration, and age-related macular degeneration.

 

Other cell populations also seem particularly prone to mobile DNA rearrangements. Several epithelial cancers, such as those lining the gastrointestinal tract, are known to harbor mobile genetic elements at diverse locations. Whether these events are at the root of the cancer or a side effect is not currently known, and the human genome is much more complex than previously thought. While jumping genes are just one part of the puzzle, scientists are beginning to appreciate the genetic contribution that microbes make to human diversity and disease.

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Antarctic krill population contracts southward as polar oceans warm

Antarctic krill are shrimp-like crustaceans which occur in enormous numbers in the cold Southern Ocean surrounding Antarctica. They have a major role in the food web and play a significant role in the transport of atmospheric carbon to the deep ocean.

Important krill habitats are under threat from climate change, and this latest research – published today in Nature Climate Change - has found that their distribution has contracted towards the Antarctic continent. This has major implications for the ecosystems that depend on krill.

An international team of scientists, led jointly by Dr Simeon Hill at the British Antarctic Survey and Dr Angus Atkinson at PML, analysed data on the amount of krill caught in nets during scientific surveys. The data covered the Scotia Sea and Antarctic Peninsula – the region where krill are most abundant. The team found that the centre of the krill distribution has shifted towards the Antarctic continent by about 440 km (4° latitude) over the last four decades.

The team took great care to account for background noise in the data.  Many factors, in addition to long-term change, influence the amount of krill caught in any one net. Even after accounting for these factors the team found a consistent trend throughout the data, indicating a substantial change in the krill population over time.

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Summer Rain on Titan: Methane Rain Falls on Titan's North Pole Even Without Clouds

Summer Rain on Titan: Methane Rain Falls on Titan's North Pole Even Without Clouds | Amazing Science | Scoop.it
Using Cassini observations, researchers have found rainfall on Titan's north pole. 

 

NASA’s Cassini orbiter captured the north pole on Saturn’s largest moon looking like a wet sidewalk after a bit of rain. This rainfall, which scientists take to signify a change in season on the moon, brought summer to Titan’s northern hemisphere earlier than scientists had predicted. This is the first time summer rainfall has ever been seen on the moon. But strangely, the rain came without any clouds.

Summer Rain on Titan

The Cassini spacecraft may be long gone, but the data it collected in its long journey continues to reveal incredible truths about Saturn and its moons. Now, researchers from the University of Idaho in Moscow have used Cassini’s observations to pinpoint rainfall on Titan’s north pole. Noticing what is described as “the wet-sidewalk effect,” the team spotted light reflecting off of Titan’s north pole in a way that indicates the presence of rainfall.

But, the team has yet to find an explanation for the rainfall’s missing clouds. “The whole Titan community has been looking forward to seeing clouds and rains on Titan’s north pole, indicating the start of the northern summer,” lead study author Rajani Dhingra from the University of Idaho told the news site BGR. “But despite what the climate models had predicted, we weren’t even seeing any clouds. People called it the curious case of missing clouds.”

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New test may catch pancreatic cancer in earlier stages

New test may catch pancreatic cancer in earlier stages | Amazing Science | Scoop.it

A new pancreatic cancer test could detect the disease before it progresses to later, deadly stages, new research says. Scientists have developed tests that pinpoints close to 70 percent of pancreatic cancer with less than 5 percent false-positive rate, according to a study published this month in Clinical Cancer Research.

 

"Pancreatic cancer is an aggressive disease made even more devastating by its tendency to spread before detection, which is a serious roadblock to successful medical treatment," Brian Haab, a professor at the Van Andel Research Institute and the study's senior author, said in a press release. "We hope that our new test, when used in conjunction with the currently available test, will help doctors catch and treat pancreatic cancer in high-risk individuals before the disease has spread."

 

Pancreatic cancer often occurs without early symptoms, making it hard to diagnose. Once doctors finally discover the disease, it's in an advanced stage making it harder to treat. In fact, the survival rate for patients with pancreatic cancer is 8.5 percent.

 

The American Cancer Society says pancreatic cancer accounts for 3 percent of all cancers and 7 percent of all cancer deaths in the U.S. Pancreatic cancer is detected by calculating the level of sugar it produces that leaks into the bloodstream. The new test, however, measures a sugar called sTRA, which comes from a different subset of pancreatic cancers. The traditional test, which measures a sugar known as CA-19-9, only confirms a pancreatic cancer diagnosis.

 

Developed 40 years ago, the CA-19-9 test only detects 40 percent of pancreatic cancers, and its only practical use is to track the progression of the disease. When used in combination, both the sTRA and CA-19-9 tests work effectively to locate the disease in its early stages.

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Without a Proof, Mathematicians Wonder How Much Evidence Is Enough

Without a Proof, Mathematicians Wonder How Much Evidence Is Enough | Amazing Science | Scoop.it
Alexander Smith’s work on the Goldfeld conjecture reveals fundamental characteristics of elliptic curves.

 

Four researchers have recently come out with a model that upends the conventional wisdom in their field. They have used intensive computational data to suggest that for decades, if not longer, prevailing opinion about a fundamental concept has been wrong.

 

These are not biologists, climatologists or physicists. They don’t come from a field in which empirical models get a say in determining what counts as true. Instead they are mathematicians, representatives of a discipline whose standard currency — indisputable logical proof — normally spares them the kinds of debates that consume other fields. Yet here they are, model in hand, suggesting that it might be time to re-evaluate some long-held beliefs.

 

The model, which was posted in 2016 and is forthcoming in the Journal of the European Mathematical Society, concerns a venerable mathematical concept known as the “rank” of an algebraic equation. The rank is a measurement that tells you something about how many of the solutions to that equation are rational numbers as opposed to irrational numbers. Equations with higher ranks have larger and more complicated sets of rational solutions.

 

Since the early 20th century mathematicians have wondered whether there is a limit to how high the rank can be. At first almost everyone thought there had to be a limit. But by the 1970s the prevailing view had shifted — most mathematicians had come to believe that rank was unbounded, meaning it should be possible to find curves with infinitely high ranks. And that’s where opinion stuck even though, in the eyes of some mathematicians, there weren’t any strong arguments in support of it.

 

“It was very authoritarian the way people said it was unbounded. But when you looked into it, the evidence seemed very slim,” said Andrew Granville, a mathematician at the University of Montreal and University College London. Now evidence points in the opposite direction. In the two years since the model was released, it has convinced many mathematicians that the rank of a specific type of algebraic equation really is bounded. But not everyone finds the model persuasive. The lack of resolution raises the kinds of questions that don’t often attend mathematical results — what weight should you give to empirical evidence in a field where all that really counts is proof?

 

“There is really no mathematical justification for why this model is exactly what we want,” said Jennifer Park, a mathematician at Ohio State University and a co-author of the work. “Except that experimentally, a lot of things seem to be working out.”

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Scientists have managed to grow perfect human blood vessels as organoids in a petri dish for the first time

Scientists have managed to grow perfect human blood vessels as organoids in a petri dish for the first time | Amazing Science | Scoop.it

The breakthrough engineering technology, outlined in a new study published today in Nature, dramatically advances research of vascular diseases like diabetes, identifying a key pathway to potentially prevent changes to blood vessels—a major cause of death and morbidity among those with diabetes.

 

An organoid is a three-dimensional structure grown from stem cells that mimics an organ and can be used to study aspects of that organ in a petri dish. “Being able to build human blood vessels as organoids from stem cells is a game changer,” said the study’s senior author Josef Penninger, the Canada 150 Research Chair in Functional Genetics, director of the Life Sciences Institute at UBC and founding director of the Institute for Molecular Biotechnology of the Austrian Academy of Sciences (IMBA).

 

“Every single organ in our body is linked with the circulatory system. This could potentially allow researchers to unravel the causes and treatments for a variety of vascular diseases, from Alzheimer’s disease, cardiovascular diseases, wound healing problems, stroke, cancer and, of course, diabetes.”

 

Diabetes affects an estimated 420 million people worldwide. Many diabetic symptoms are the result of changes in blood vessels that result in impaired blood circulation and oxygen supply of tissues. Despite its prevalence, very little is known about the vascular changes arising from diabetes. This limitation has slowed the development of much-needed treatment.

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Google’s AI Can Help Predict Where Earthquake Aftershocks Are Most Likely

Google’s AI Can Help Predict Where Earthquake Aftershocks Are Most Likely | Amazing Science | Scoop.it

The destruction that a large earthquake can cause often doesn’t end when the ground stops shaking. Many produce aftershocks, smaller tremors hours or even days later caused by the ground’s reaction to the first quake.

 

These aftershocks can sometimes cause more damage than the primary quake. And though we can usually predict the size of an aftershock, we haven’t been so great at predicting its location.

Now, that could change. Researchers from Harvard University and Google’s AI division have created a neural network that can assess how likely it is that a particular location will experience an aftershock. The best part? It’s more accurate than the best existing models.

 

They published their study Wednesday in the journal Nature.

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Scientists Are Warning: Warming Oceans Will Lead to a “Catastrophic” Future

Scientists Are Warning: Warming Oceans Will Lead to a “Catastrophic” Future | Amazing Science | Scoop.it

new study in the journal Science has found that the Earth’s oceans are warming far faster than experts had previously predicted, leading to a bleak outlook among climate scientists who say the rapid environmental shifts will lead to international disputes, humanitarian crises and deadly freak weather events.

 

The New York Times, for instance, summarized researchers’ view of the findings as “catastrophic.” “It’s spilling over far beyond just fish, it’s turned into trade wars,” Rutgers professor Malin Pinsky told the newspaper. “It’s turned into diplomatic disputes. It’s led to a breakdown in international relations in some cases.” As the greenhouse effect has intensified, according to the new research, the oceans have born the brunt of global warming. Readings suggest that 2018 will be the hottest year on record for the planet’s seas, replacing 2017 and 2016 before it.

 

The effects for weather patterns and marine life are dire, experts warn — and food shortages and displacement will leak into geopolitics long before we scorch life above the waterline as well.

“If the ocean wasn’t absorbing as much heat, the surface of the land would heat up much faster than it is right now,” Pinsky told the Times. “In fact, the ocean is saving us from massive warming right now.”

 

READ MORE: Ocean Warming Is Accelerating Faster Than Thought, New Research Finds [The New York Times]

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AI Can Make Sure Cancer Patients Get Just Enough (but Not Too Much) Treatment

AI Can Make Sure Cancer Patients Get Just Enough (but Not Too Much) Treatment | Amazing Science | Scoop.it

Patients with glioblastoma, a malignant tumor in the brain or spinal cord, typically live no more than five years after receiving their diagnosis. And those five years can be painful — in an effort to minimize the tumor, doctors often prescribe a combination of radiation therapy and drugs that can cause debilitating side effects for patients.

 

Now, researchers from MIT Media Lab have developed artificial intelligence (AI) that can determine the minimum drug doses needed to effectively shrink glioblastoma patients’ tumors. They plan to present their research at Stanford University’s 2018 Machine Learning for Healthcare conference.

 

To create an AI that could determine the best dosing regimen for glioblastoma patients, the MIT researchers turned to a training technique known as reinforcement learning (RL). First, they created a testing group of 50 simulated glioblastoma patients based on a large dataset of those that had previously undergone treatment for their disease. Then they asked their AI to recommend doses of several drugs typically used to treat glioblastoma [oftemozolomide (TMZ) and a combination of procarbazine, lomustine, and vincristine (PVC)] for each patient at regular intervals (either weeks or months).

 

After the AI prescribed a dose, it would check a computer model capable of predicting how likely a dose is to shrink a tumor. When the AI prescribed a tumor-shrinking dosage, it received a reward. However, if the AI simply prescribed the maximum dose all the time, it received a penalty. According to the researchers, this need to strike a balance between a goal  and the consequences of an action — in this case, tumor reduction and patient quality of life respectively — is unique in the field of RL. Other RL models simply work toward a goal; for example, DeepMind’s AlphaZero simply has to focus on winning a game.

 

“If all we want to do is reduce the mean tumor diameter, and let it take whatever actions it wants, it will administer drugs irresponsibly,” principal investigator Pratik Shah told MIT News. “Instead, we said, ‘We need to reduce the harmful actions it takes to get to that outcome.’”

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A new method uses ultrashort deep-ultraviolet pulses to accurately probe real-time chirality changes in (bio)molecular systems

A new method uses ultrashort deep-ultraviolet pulses to accurately probe real-time chirality changes in (bio)molecular systems | Amazing Science | Scoop.it

Distinguishing between left-handed and right-handed (“chiral”) molecules is crucial in chemistry and the life sciences, and is commonly done using a method called circular dichroism. However, during biochemical reactions the chiral character of molecules may change. EPFL scientists have for the first time developed a method that uses ultrashort deep-ultraviolet pulses to accurately probe such changes in real-time in (bio)molecular systems.

 

In nature, certain molecules with the same chemical composition, can exist in two different shapes that are mirrors images of each other, much like our hands. This property is known as “chirality” and molecules with different chirality are called enantiomers. Enantiomers can exhibit entirely different chemical or biological properties, and separating them is a major issue in drug development and in medicine.

 

The method commonly used to detect enantiomers is circular dichroism (CD) spectroscopy. It exploits the fact that light polarized into a circular wave (like a whirlpool) is absorbed differently by left-handed and right-handed enantiomers. Steady-state CD spectroscopy is a major structural tool in (bio)chemical analysis.

 

During their function, biomolecules undergo structural changes that affect their chiral properties. Probing these in real-time (i.e. between 1 picosecond and 1 nanosecond) provides a view of their biological function, but this has been challenging in the deep-UV spectrum (wavelengths below 300 nm) where most biologically relevant molecules such as amino acids, DNA and peptide helices absorb light.

 

The limitations are due to the lack of adequate sources of pulsed light and of sensitive detection schemes. But now, the group of Majed Chergui at the Lausanne Centre for Ultrafast Science (EPFL) has developed a setup that allows the visualization of the chiral response of (bio)molecules by CD spectroscopy with a resolution of 0.5 picoseconds.

 

The setup uses a photoelastic modulator, which is an optical device that can control the polarization of light. In this system, the modulator permits shot-to-shot polarization switching of a 20 kHz femtosecond pulse train in the deep-UV range (250–370 nm). It is then possible to record changes in the chirality of molecules at variable time-delays after they are excited with a short laser pulse.

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First Direct Evidence That Stars Like Our Sun Turn Into Crystals In The Final Stages Of Their Lives

First Direct Evidence That Stars Like Our Sun Turn Into Crystals In The Final Stages Of Their Lives | Amazing Science | Scoop.it

Fifty years after the idea was proposed, astronomers find direct evidence that white dwarfs - the dense, stellar corpses of sun-like stars - can crystallize.

 

Stars like our sun can turn into crystals in the final stages of their lives, bringing a whole new meaning to those glittering jewels in the sky. Astronomers from the University of Warwick say they’ve found the first direct evidence that white dwarf stars – the dense, stellar corpses of stars like our sun – can crystallize, or turn from a liquid into a solid. The discovery was published Wednesday in the journal Nature.

 

Astronomers had long suspected such crystallization was possible. But to find direct evidence, the team turned to data gathered by the European Space Agency’s Gaia satellite and analyzed some 15,000 white dwarf candidates. In the process, they uncovered a “pile-up” of stars with colors and luminosities that matched those predicted for crystallized white dwarfs.

 

The discovery, led by physicist Pier-Emmanuel Tremblay, was announced exactly 50 years after it was first predicted. “All white dwarfs will crystallize at some point in their evolution,” Tremblay said in a media release. “This means that billions of white dwarfs in our galaxy have already completed the process and are essentially crystal spheres in the sky. The sun itself will become a crystal white dwarf in about 10 billion years.”

 

White dwarfs are extremely dense stars, so the positively charged nuclei in their cores exist as a fluid, the scientists say. But as the star cools, that fluid solidifies and creates a metal core. And because white dwarfs are among our cosmos’ oldest stellar objects, with predictable life stages, astronomers often use them as “clocks” to date surrounding groups of stars. So understanding this crystallization process could bring greater accuracy when scientists assign ages to the stars.

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Dark Energy Survey completes six-year mission

Dark Energy Survey completes six-year mission | Amazing Science | Scoop.it

After six years of scanning in depth about a quarter of the southern skies, and cataloguing hundreds of millions of distant galaxies, the Dark Energy Survey will finish taking data tomorrow.

 

DES is an international collaboration that began mapping a 5000-square-degree area of the sky on August 31, 2013, in a quest to understand the nature of dark energy, the mysterious force that is accelerating the expansion of the universe. Using the Dark Energy Camera, a 520-megapixel digital camera mounted on the Blanco 4-meter telescope at the National Science Foundation’s Cerro Tololo Inter-American Observatory in Chile, scientists on DES took data on a total of 758 nights.

 

Over those nights, they recorded data from a few hundred million distant galaxies. More than 400 scientists from over 25 institutions around the world have been involved in the project, which is hosted by the US Department of Energy’s Fermi National Accelerator Laboratory. The collaboration has already produced about 200 academic papers, with more to come.

 

According to DES Director Rich Kron, a Fermilab and University of Chicago scientist, those results and the scientists who made them possible are where much of the real accomplishment of DES lies. “First generations of students and post-doctoral researchers on DES are now becoming faculty at research institutions and are involved in upcoming sky surveys,” Kron says. “The number of publications and people involved are a true testament to this experiment. Helping to launch so many careers has always been part of the plan, and it’s been very successful.”

 

DES remains one of the most sensitive and comprehensive surveys of distant galaxies ever performed. The Dark Energy Camera is capable of seeing light from galaxies billions of light-years away, capturing it in unprecedented quality.  According to Alistair Walker of the National Optical Astronomy Observatory, a DES team member and the Blanco telescope scientist, equipping the telescope with the Dark Energy Camera transformed it into a state-of-the-art survey machine. 

 

“DECam was needed to carry out DES, but it also created a new tool for discovery, from the Solar System to the distant universe,” Walker says. “For example, 12 new moons of Jupiterwere recently discovered with DECam, and the detection of distant star-forming galaxies in the early universe, when the universe was only a few percent of its present age, has yielded new insights into the end of the cosmic dark ages.”

 

The survey generated 50 terabytes (that’s 50 million megabytes) of data over its six observation seasons. That data is stored and analyzed at the National Center for Supercomputing Applications at the University of Illinois Urbana-Champaign. “As observations end, NCSA is proud to continue supporting the science productivity of the collaboration by making refined data releases and serving the data well into to 2020s,” says Don Petravick, principal investigator for the Dark Energy Survey data management team at NCSA.

 

Now the job of analyzing that data takes center stage. DES has already released a full range of papers based on its first year of data, and scientists are now diving into the rich seam of cataloged images from the first several years of data, looking for clues to the nature of dark energy. The first step in that process, according to Fermilab and University of Chicago scientist Josh Frieman, former director of DES, is to find the signal in all the noise. “We’re trying to tease out the signal of dark energy against a background of all sorts of non-cosmological stuff that gets imprinted on the data,” Frieman says. “It’s a massive ongoing effort from many different people around the world.” 

 

The DES collaboration continues to release scientific results from their storehouse of data. Highlights from the previous years include:

 

DES scientists also spotted the first visible counterpart of gravitational waves ever detected, a collision of two neutron stars that occurred 130 million years ago. DES was one of several sky surveys that detected this gravitational-wave source, opening the door to a new kind of astronomy. Recently DES issued its first cosmology results based on supernovae (207 of them taken from the first three years of DES data), using a method which 20 years ago provided the first evidence for cosmic acceleration. More comprehensive results on dark energy are expected within the next few years.

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How do Aliens See us? One-Pixel Views of Earth Reveal Seasonal Changes

How do Aliens See us? One-Pixel Views of Earth Reveal Seasonal Changes | Amazing Science | Scoop.it
By averaging satellite images of the Earth down to a single pixel, researchers trace how the planet’s mean color varies over time, results that inform observations of distant exoplanets.

 

When Al Gore, then U.S. vice president, originally proposed the Deep Space Climate Observatory (DSCOVR) satellite in 1998, he hoped that its detailed images of the Earth’s surface would inspire the public. They have, and now scientists are finding a novel use for these satellite observations that Gore probably never imagined: studying exoplanets. By averaging thousands of high-resolution DSCOVR images down to just one pixel each, a team of scientists was able to determine how the Earth’s average color varies over a year. The team also compared the data with models of the Earth to reveal how environmental conditions like clouds and snow modulate the appearance of distant exoplanets. These results were presented this week at the 233rd Meeting of the American Astronomical Society, held in Seattle, Wash.

 

You can mimic what Earth might look like from very far away.

 Aronne Merrelli, an atmospheric scientist at the Space Science and Engineering Center at the University of Wisconsin–Madison, and his colleagues collected over 5,000 images of the sunlit side of the Earth taken in 2016 by the Earth Polychromatic Imaging Camera (EPIC) on board DSCOVR. The researchers repurposed these EPIC data, which were originally intended to reveal information about the planet’s ozone levels, aerosols suspended in the atmosphere, clouds, and vegetation. “We just smash it down to one pixel,” said Merrelli of the data spanning the ultraviolet, visible, and infrared. “We’re throwing away a lot of information.” This single-pixel view of the Earth is similar to the resolution scientists have of distant planets orbiting other stars, said Merrelli. “You can mimic what Earth might look like from very far away.”

 

The researchers—a mix of Earth scientists and astronomers—then examined how the planet’s average color varied over seasons. They found that Earth tended to be redder from June through September, probably because of the increase in vegetation in the Northern Hemisphere and a reduction in snow cover.

 

Merrelli and his team also compared the EPIC observations with a model of the Earth’s surface with its current configuration of landmasses and oceans and varying amounts of clouds, snow, and sea ice. These simulations allowed the scientists to determine the impact of dynamic environmental conditions on the planet’s color. They found that clouds played a large role in dictating the planet’s average color. “This type of investigation definitely lays the groundwork for imaging of Earth-like exoplanets,” said Drake Deming, an astronomer at the University of Maryland not involved in the research.

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