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Chemists create ‘artificial chemical evolution’ for the first time

Chemists create ‘artificial chemical evolution’ for the first time | Amazing Science | Scoop.it

Scientists have taken an important step towards the possibility of creating synthetic life with the development of a form of artificial evolution in a simple chemistry set without DNA.


A team from the University of Glasgow’s School of Chemistry report in a new paper in the journal Nature Communications today (Monday 8 December) on how they have managed to create an evolving chemical system for the first time. The process uses a robotic ‘aid’ and could be used in the future to ‘evolve’ new chemicals capable of performing specific tasks.


The researchers used a specially-designed open source robot based upon a cheap 3D printer to create and monitor droplets of oil in water-filled Petri dishes in their lab. Each droplet was composed from a slightly different mixture of four chemical compounds.


Droplets of oil move in water like primitive chemical machines, transferring chemical energy to kinetic energy. The researchers’ robot used a video camera to monitor, process and analyse the behaviour of 225 differently-composed droplets, identifying a number of distinct characteristics such as vibration or clustering.


The team picked out three types of droplet behavior – division, movement and vibration – to focus on in the next stage of the research. They used the robot to deposit four droplets of the same composition, then ranked the droplets in order of how closely they fit the criteria of behaviour identified by the researchers. The chemical composition of the ‘fittest’ droplet was then carried over into a second generation of droplets, and the process of robotic selection was begun again.

Over the course of 20 repetitions of the process, the researchers found that the droplets became more stable, mimicking the natural selection of evolution.


The research team was led by Professor Lee Cronin, the University of Glasgow’s Regius Chair of Chemistry. Professor Cronin said: “This is the first time that an evolvable chemical system has existed outside of biology. Biological evolution has given rise to enormously complex and sophisticated forms of life, and our robot-driven form of evolution could have the potential to do something similar for chemical systems.

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Optical detection of picomolar concentrations of RNA using switches in plasmonic chirality

Optical detection of picomolar concentrations of RNA using switches in plasmonic chirality | Amazing Science | Scoop.it
Even tiny amounts of viruses can have disastrous consequences. RNA identification can reveal the type of virus present. A fast and sensitive technique based on optical detection has now been outlined in the journal Angewandte Chemie. Scientists from Germany and Finland have demonstrated the binding of an RNA target to a probe made of gold nanorods and a DNA origami structure. Chirality switches triggered by binding can be measured by circular dichroism spectroscopy.

Identifying the pathogen—often a virus—that is troubling a patient is among the biggest challenges in healthcare. Viruses responsible for Zika fever, AIDS, and hepatitis C contain mutating RNA sequences. Physicians need to know quickly which type of virus their patients have acquired, but current techniques based on multiplying RNA are costly and time-consuming. Now, Tim Liedl from Ludwigs-Maximilians-Universität in Munich, Germany, and his colleagues, have developed a fast detection strategy based on nanoplasmonics, DNA origami, and an optical readout.

Light can induce plasmonic waves in nanosized metal structures smaller than the wavelength of the incident light. This resonance may lead to strongly enhanced light emission even from nanoscopic structures—a feature that is highly interesting for biosensing applications. Liedl and colleagues have created a nanosized sensing probe for RNA molecules.

The probe, a nanosized apparatus made of DNA and gold nanorods, was assembled by the so-called DNA origami technique, which exploits the specific interactions of the DNA bases to fold and glue together single strands in any desired form. The authors constructed two bars of parallel DNA helices loosely connected through a hinge in the middle of the bars. Gold nanorods were placed on top of each of the crossed bars. Both crossing arms were supplied with functionality at their ends: the scientists attached one single DNA sequence complemented with a blocking strand to one arm, and the complementing DNA sequence to the other. In the presence of target RNA, which could be a typical viral RNA sequence, the blocking strand would leave its DNA in favor of RNA hybridization, and both single DNA sequences would complementarily form a double strand whereby the two arms of the cross are pulled together. This structural change introduces chirality to the probe.
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Gut bacteria’s shocking secret: They produce electricity

Gut bacteria’s shocking secret: They produce electricity | Amazing Science | Scoop.it

Electrogenic ability may be important in how bacteria infect humans, or in how they ferment cheese and yogurt,

 

While bacteria that produce electricity have been found in exotic environments like mines and the bottoms of lakes, scientists have missed a source closer to home: the human gut. University of California, Berkeley, scientists discovered that a common diarrhea-causing bacterium, Listeria monocytogenes, produces electricity using an entirely different technique from known electrogenic bacteria, and that hundreds of other bacterial species use this same process.

 

Many of these sparking bacteria are part of the human gut microbiome, and many, like the bug that causes the food-borne illness listeriosis, which can also cause miscarriages, are pathogenic. The bacteria that cause gangrene (Clostridium perfringens) and hospital-acquired infections (Enterococcus faecalis) and some disease-causing streptococcus bacteria also produce electricity. Other electrogenic bacteria, like Lactobacilli, are important in fermenting yogurt, and many are probiotics.

 

"The fact that so many bugs that interact with humans, either as pathogens or in probiotics or in our microbiota or involved in fermentation of human products, are electrogenic -- that had been missed before," said Dan Portnoy, a UC Berkeley professor of molecular and cell biology and of plant and microbial biology. "It could tell us a lot about how these bacteria infect us or help us have a healthy gut."

 

The discovery will be good news for those currently trying to create living batteries from microbes. Such "green" bioenergetic technologies could, for example, generate electricity from bacteria in waste treatment plants.

 

The research will be posted online Sept. 12, 2018 in advance of Oct. 4, 2018 print publication in the journal Nature.

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Scuba spider uses web as gill to breathe underwater

Scuba spider uses web as gill to breathe underwater | Amazing Science | Scoop.it

Using its web as a gill, the diving-bell spider can live underwater with only occasional visits to the surface. The arachnid (Argyroneta aquatica) breathes air from a bubble that it grabs from the surface of water using fine hairs on its abdomen. The spider traps the air within a bell-shaped silken web that it constructs underwater and carries around like an aqualung.

 

It was first described over 250 years ago, but until now biologists didn’t know how it managed to remain underwater without frequent visits to the surface to renew the oxygen in its tiny air bubble.

 

To find out, Roger Seymour from the University of Adelaide in South Australia and Stefan Hetz of Humboldt University in Berlin, Germany, placed 12 spiders in individual aquaria and measured the oxygen levels within the air bubbles using optical fibres tipped with oxygen-sensitive dye. Seymour also measured the concentration of oxygen in the water outside the bubble.

 

“The spider’s web acts like a gill,” says Seymour. The silken web allows oxygen to diffuse from the surrounding water into the depleted air, as well as release carbon dioxide.

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Russian android robot F.e.d.o.r to acquire self-learning abilities

Russian android robot F.e.d.o.r to acquire self-learning abilities | Amazing Science | Scoop.it

The Russian android robot called F.e.d.o.r (Fedor) can do the splits and screw in a light bulb, CEO of Android Technics Research and Production Association Alexander Permyakov told TASS recently. Android Technics is the developer of the robot Fedor. The chief executive confirmed that the robot could do the splits to demonstrate its technical capabilities. Moreover, it can stand on one leg, having vertically lifted the other.

 

"Our chassis allows doing this. However, as part of the tests, this technical possibility did our robot a service when it had to overcome an obstacle," the Android Technics CEO said. The Russian robot also has mobile fingers, he said. "A manipulator has been created but hundreds and, perhaps, thousands of programmers’ work hours are needed to sharpen fine motor skills," he said. "We can also mention the robot’s ability to screw in a light bulb as an example of our own scientific and technical potential, which we have developed beyond the requirements of the Rescuer project," he added.

 

Besides, the robot’s fine motor skills allow Fedor to insert the key in the lock, open the door of an apartment, switch on the light and drive a car. Fedor has been developed by Android Technics and the Advanced Research Fund under a technical assignment from Russia’s Emergencies’ Ministry. Originally, the robot was known under the notional name of Avatar but it has recently received is own name FEDOR, which stands for Final Experimental Demonstration Object Research.

 

Apart from the Rescuer project in the interests of the Emergencies Ministry, the robot will be able to perform other assignments. Thus, the android is set to become the sole passenger of Russia’s new spacecraft Federatsiya in 2021 during the spaceship’s first flight. The Russian robot will be technically simplified before it is serially produced, the chief executive said.

 

"The robot will be serially produced in a long-term perspective even in very large numbers but today what is required is to simplify the design and increase the robot’s service life. That is, it will be produced in a simplified form in the short-term perspective," the Android Technics CEO said.

 
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The story of moonshine symmetry, number theory, and the monster

The story of moonshine symmetry, number theory, and the monster | Amazing Science | Scoop.it

In 1978, the mathematician John McKay noticed what seemed like an odd coincidence. He had been studying the different ways of representing the structure of a mysterious entity called the monster group, a gargantuan algebraic object that, mathematicians believed, captured a new kind of symmetry. Mathematicians weren’t sure that the monster group actually existed, but they knew that if it did exist, it acted in special ways in particular dimensions, the first two of which were 1 and 196,883.

 

McKay, of Concordia University in Montreal, happened to pick up a mathematics paper in a completely different field, involving something called the j-function, one of the most fundamental objects in number theory. Strangely enough, this function’s first important coefficient is 196,884, which McKay instantly recognized as the sum of the monster’s first two special dimensions.

 

Most mathematicians dismissed the finding as a fluke, since there was no reason to expect the monster and the j-function to be even remotely related. However, the connection caught the attention of John Thompson, a Fields medalist now at the University of Florida in Gainesville, who made an additional discovery. The j-function’s second coefficient, 21,493,760, is the sum of the first three special dimensions of the monster: 1 + 196,883 + 21,296,876. It seemed as if the j-function was somehow controlling the structure of the elusive monster group.

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A massive net is being deployed to pick up plastic in the Pacific

A massive net is being deployed to pick up plastic in the Pacific | Amazing Science | Scoop.it
 

The days of the great Pacific garbage patch may be numbered. A highly anticipated project to scoop up plastic from the massive pool of ocean debris is poised to launch its first phase from Alameda, Calif., on September 8. The creators of the project, called the Ocean Cleanup, say their system can remove 90 percent of the plastic in the patch by 2040.

 

First proposed in a 2012 TED talk by Dutch-born inventor Boyan Slat, who was then just 18 years old, the Ocean Cleanup’s system consists of a snaking line of booms designed to simulate a kind of free-floating coastline that can essentially herd the plastic trash into retrievable piles. The project, based in Delft, the Netherlands, has drawn more than $30 million in donations from sponsors, philanthropists and a crowdfunding campaign.

 

It has also drawn the ire of researchers who worry about possible negative effects on ocean life, or who say the project doesn’t address the majority of ocean plastic — bits called microplastics that are smaller than half a centimeter. The system is designed to capture pieces of plastic ranging in size from a few millimeters to tens of meters across, such as fishing nets. Critics also worry the project will divert attention and money from the root of the problem: too much plastic waste in the first place.

Ready for launch

A March study in Scientific Reports, led by Ocean Cleanup’s lead oceanographer Laurent Lebreton, estimated that in 2015 the great Pacific garbage patch was scattered across some 1.6 million square kilometers — an area twice the size of Texas — within a vast ocean swirl known as the North Pacific gyre. The patch, the study found, contains about 1.8 trillion pieces of debris, largely consisting of buoyant plastics like polyethylene and polypropylene, floating at the surface. Most of those pieces are smaller than half a centimeter — but by mass, more than 90 percent of the patch is made up of pieces 5 centimeters or bigger, the scientists estimate.

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Globally, 1.4 billion adults at risk of disease from not doing enough physical activity

Globally, 1.4 billion adults at risk of disease from not doing enough physical activity | Amazing Science | Scoop.it

More than a quarter (1.4 billion) of the world's adult population were insufficiently active in 2016, putting them at greater risk of cardiovascular disease, type 2 diabetes, dementia, and some cancers, according to the first study to estimate global physical activity trends over time. The study was undertaken by researchers from the World Health Organization (WHO) and published in The Lancet Global Healthjournal.

 

Together, these estimates demonstrate that there has been little progress in improving physical activitylevels between 2001 and 2016. The data show that if current trends continue, the 2025 global activity target of a 10% relative reduction in insufficient physical activity will not be met.

 

"Unlike other major global health risks, levels of insufficient physical activity are not falling worldwide, on average, and over a quarter of all adults are not reaching the recommended levels of physical activity for good health," warns the study's lead author, Dr. Regina Guthold of the WHO, Switzerland.

 

In 2016, around one in three women (32%) and one in four men (23%) worldwide were not reaching the recommended levels of physical activity to stay healthy—ie, at least 150 minutes of moderate-intensity, or 75 minutes of vigorous-intensity physical activity per week.

 

The new study is based on self-reported activity levels, including activity at work and at home, for transport, and during leisure time, in adults aged 18 years and older from 358 population-based surveys in 168 countries, including 1.9 million participants.

 

Among the study's main findings were:

  • In 2016, levels of insufficient activity among adults varied widely across income groups—16% in low-income countries compared to 37% in high-income countries.
  • In 55 (33%) of 168 countries, more than a third of the population was insufficiently physically active.
  • In four countries, more than half of adults were insufficiently active—Kuwait (67%), American Samoa (53%), Saudi Arabia (53%), and Iraq (52%).
  • Countries with the lowest levels of insufficient physical activity in 2016 were Uganda and Mozambique (6% each).
  • Women were less active than men in all regions of the world, apart from east and southeast Asia. In 2016, there was a difference in levels of insufficient activity between women and men of 10 percentage points or more in three regions: South Asia (43% vs 24%), Central Asia, Middle East and north Africa (40% vs 26%), and high-income Western countries (42% vs 31%).
  • Across regions, many individual countries recorded large differences in insufficient activity between women and men. Examples include Bangladesh (40% vs 16%), Eritrea (31% vs 14%), India (44% vs 25%), Iraq (65% vs 40%), Philippines (49% vs 30%), South Africa (47% vs 29%), Turkey (39% vs 22%), the USA (48% vs 32%), and the UK (40% vs 32%).
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Going up! Japan to test mini 'space elevator'

Going up! Japan to test mini 'space elevator' | Amazing Science | Scoop.it
A Japanese team working to develop a "space elevator" will conduct a first trial this month, blasting off a miniature version on satellites to test the technology.

 

 

The test equipment, produced by researchers at Shizuoka University, will hitch a ride on an H-2B rocket being launched by Japan's space agency from southern island of Tanegashima next week. The test involves a miniature elevator stand-in—a box just six centimeters (2.4 inches) long, three centimeters wide, and three centimeters high. If all goes well, it will provide proof of concept by moving along a 10-meter cable suspended in space between two mini satellites that will keep it taut.bThe mini-elevator will travel along the cable from a container in one of the satellites.

 

"It's going to be the world's first experiment to test elevator movement in space," a university spokesman told AFP on Tuesday. The movement of the motorized "elevator" box will be monitored with cameras in the satellites. It is still a far cry from the ultimate beam-me-up goals of the project, which builds on a long history of "space elevator" dreams.

 

The idea was first proposed in 1895 by Russian scientist Konstantin Tsiolkovsky after he saw the Eiffel Tower in Paris, and was revisited nearly a century later in a novel by Arthur C. Clarke. But technical barriers have always kept plans stuck at the conceptual stage. Japanese construction firm Obayashi, which is collaborating with the Shizuoka university project, is also exploring other ways to build its own space elevator to put tourists in space in 2050. The company has said it could use carbon nanotube technology, which is more than 20 times stronger than steel, to build a lift shaft 96,000 kilometers (roughly 60,000 miles) above the Earth.

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Demystifying Convolutional Neural Networks: How a Deep Neural Network Sees

Simply put, a Convolutional Neural Network is a Deep learning model or a multilayered percepteron similar to Artificial Neural Networks which is most commonly applied to analyzing visual imagery. The founding father of Convolutional Neural Networks is the well known computer scientist working in Facebook Yann LeCun who was the first one to use them to solve the hand written digits problem using the famous MNIST Dataset.

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Festo's Flying Animal Robots Are Real and Magnificent

Festo's Flying Animal Robots Are Real and Magnificent | Amazing Science | Scoop.it
They put even the coolest drones to shame.

 

Just barely making it under the wire of a year full of bizarre and adorable robots, the fancy animal robot-makers at Festo are back with three new flying robots. An industrial automation company, Festo's robotic menagerie also includes herring gulls, kangaroos, ants, an elephant's trunk, and a gripper inspired by the tongue of a chameleon. Festo showed off three new animalistic flying drones at the USA Science and Engineering Festival in Washington, DC last summer, and they can seen beautifully gliding through the air in a video captured by IEEE Spectrum.

 

The eMotionButterfly uses a camera tracking system to fly autonomously, avoiding crashes into the ceiling and walls without human guidance. A kaleidoscope of up to 15 butterflies can work together at once, using the tracking cameras to navigate without crashing into one another.

 

AirJelly, a giant flying jellyfish, is gently propelled up and down by eight tentacles and directed remotely with a bearing inside the helium body. It only weighs about two pounds, and can fly for two hours on one small battery.

 

Last but not least, the AirPenguin is a chubby silver blimp-bot with flippers that help it glide forward through the air, and moveable tail fins and a beak. Each of these creatures seems plucked from alternate reality, where mechanical zoos and Atomic Age-style penguins reign the skies. We'll allow it, even though real penguins don't fly.

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How a Tiny Bacterium Called Wolbachia Could Defeat Dengue

How a Tiny Bacterium Called Wolbachia Could Defeat Dengue | Amazing Science | Scoop.it

Scientists are fighting dengue fever with the help of Wolbachia, a common bacterium that stops the virus from replicating inside the mosquitoes that transmit the disease. Without it, we have few weapons against dengue. Although the bacterium is common among insects, it does not infect Aedes aegypti, a species of mosquito that is a major carrier of dengue. Instead researchers infect the mosquito with Wolbachia in the laboratory and then release A. aegypti into the wild. The goal is to reduce infections in humans by getting Wolbachia-infected mosquitoes to mate and pass the bacterium to future generations. If the method works, vast numbers of wild mosquitoes will eventually carry Wolbachia and thus be unable to transmit dengue.

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Quantum bugs, meet your new swatter

Quantum bugs, meet your new swatter | Amazing Science | Scoop.it
A Rice University computer scientist and his colleagues have proposed a scalable algorithm for quantum state tomography to significantly accelerate the imposing task of validating the accuracy of quantum computers.

 

Anastasios Kyrillidis, an assistant professor of computer science who joined Rice this year, led the development of a nonconventional method as a diagnostic tool for powerful, next-generation computers that depend on the spooky actions of quantum bits -- aka qubits -- which are switches that operate under rules that differ from the 1s and 0s in classical computers.

Quantum computers exploit the principles of quantum mechanics to quickly solve tough problems that would take far longer on conventional supercomputers. They promise future breakthroughs in drug design, advanced materials, cryptography and artificial intelligence.

 

An open-access paper by Kyrillidis and his team appears in the Nature journal Quantum Information. Like any new hardware, Kyrillidis said, quantum computer systems are prone to bugs that need to be squashed. That takes continuous testing to validate their capabilities. The sheer complexity of quantum computers that do exponentially more with every bit requires an immense amount of validation, he said.

 

Kyrillidis' method focuses on quantum state tomography, a process inspired by medical tomography in which images of a body are captured in slices that are later reassembled into a three-dimensional map. Quantum state tomography differs, he said, as it takes "images" of the state of a quantum computer's qubits.

"When a quantum computer executes an algorithm, it starts at a specific state; think of it as the input to the algorithm," Kyrillidis said. "As the computer progresses through steps of the algorithm, it's going through many states. The state at the very end is the answer to your algorithm's question."

 

By reassembling the full state from these measurements, Kyrillidis said one can later pinpoint hardware or software errors that may have caused the computer to deliver unexpected results.

That takes a lot of measurements, and the computational cost of reconstruction can be high, even for classical computers, he said. Tomography-based analysis of quantum computers with even as few as five or six qubits would be prohibitive without somehow simplifying the task -- and state-of-the-art machines have 50 qubits or more.

 

Qubits are the basic units of information in a quantum computer. Like a bit in a classical computer, each qubit can represent either 1 or 0. Unlike a bit, a qubit can also represent 1 and 0 simultaneously, a state called superposition that exponentially raises the number of calculations an array of qubits can perform at once. To make it more interesting, the state of the qubit as determined by magnetic polarization or electron spin only exists when it's measured. Kyrillidis said even a modest increase in the number of qubits in a computer dramatically increases its power.

 

"In a system with five qubits, the state can be represented by a 2-to-the-5 times 2-to-the-5 matrix, so it's a 32-by-32 matrix," he said. "That's not big. But in a 20-qubit system like the one at IBM, the state can be characterized by a million-by-million matrix. If we were taking full measurements with regular tomography techniques, we would need to poll the system roughly a million-squared times in order to get enough information to recover its state."

 

Kyrillidis and his team solved the validation problem with an algorithm they call Projected Factored Gradient Decent (ProjFGD). It takes advantage of compressed sensing, a method that minimizes the amount of incoming data while still ensuring accurate results. He said the method would cut the number of measurements for a 20-qubit system to a mere million or so. "That's still a big number, but much smaller than a million squared," he said.

 

Kyrillidis noted that IBM, where he spent a year as a research scientist before coming to Rice, has put a quantum computer in the cloud where anyone can access it and run programs. He said the company reasons that the more people learn about programming for quantum computers now, the more mature their skills will be when the platform comes of age. But there's a side benefit for him, as it gives him a ready platform to test ProjFGD.

 

"The quantum state tomography tool is generic, and has more to do with the nature of the qubit rather than the specific architecture," Kyrillidis said. "As quantum computers get more powerful, it can definitely be scaled up to certify systems."

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Engineers develop the first method for controlling nanomotors

Engineers develop the first method for controlling nanomotors | Amazing Science | Scoop.it

In a breakthrough for nanotechnology, engineers at The University of Texas at Austin have developed the first method for selecting and switching the mechanical motion of nanomotors among multiple modes with simple visible light as the stimulus.

 

The capability of mechanical reconfiguration could lead to a new class of controllable nanoelectromechanical and nanorobotic devices for a variety of fields including drug delivery, optical sensing, communication, molecule release, detection, nanoparticle separation and microfluidic automation.

 

The finding, made by Donglei (Emma) Fan, associate professor at the Cockrell School of Engineering's Department of Mechanical Engineering, and Ph.D. candidate Zexi Liang, demonstrates how, depending on the intensity, light can instantly increase, stop and even reverse the rotation orientation of silicon nanomotors in an electric field. This effect and the underlying physical principles have been unveiled for the first time. It switches mechanical motion of rotary nanomotors among various modes instantaneously and effectively.

 

The researchers published their findings in the Sept. 14 issue of Science Advances. Nanomotors, which are nanoscale devices capable of converting energy into movement at the cellular and molecular levels, have the potential to be used in everything from drug delivery to nanoparticle separation.

 

Using light from a laser or light projector at strengths varying from visible to infrared, the UT researchers' novel technique for reconfiguring the motion of nanomotors is efficient and simple in its function. Nanomotors with tunable speed have already been researched as drug delivery vessels, but using light to adjust the mechanical motions has far wider implications for nanomotors and nanotechnology research more generally.

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Self-flying glider 'learns' to soar like a bird

Self-flying glider 'learns' to soar like a bird | Amazing Science | Scoop.it

Scientists have created a self-flying glider that uses machine learning to navigate rising air currents, in an experiment that could help our understanding of how birds migrate.

 

Soaring birds ride warm air passages known as thermals to fly and gain height without needing to flap their wings, although no one knows exactly how they do it.

 

To gain insight into what cues birds instinctively use to catch an updrafts, researchers from the University of California San Diego equipped a pilotless glider with an on-board computer allowing it to change direction on the basis of real-time measurements.

 

To help navigate the ever-changing environment, they used machine learning—the glider, which has a wingspan of two meters (six feet), in effect teaches itself how to fly by evaluating each variation in air currents and receiving a reward for every "correct" decision that resulted in increased altitude.

 

In a study published Wednesday in the journal Nature, the team reported that after just 15 hours of test flights, the glider had "learned" how to optimize its position and developed a strategy to catch the warm updrafts. "We find it very impressive as the glider had no prior knowledge about atmospheric physics or aerodynamics," Massimo Vergassola, lead study author, told AFP.

 

Whereas several other studies have shown how fast machines can learn strategies or form algorithms to solve complex problems, thermal updrafts change nearly constantly, making the gliders' task extra taxing.

 

By studying how the glider learned to respond to physical stimulus in flight, Vergassola and his colleagues believe that birds might also take certain physical and visual clues to help them climb thermals, saving vital energy needed for long migrations.

 

Species such as the bar-tailed godwit and shorebird, that can fly upward of 11,500 kilometers (7,145 miles) without stopping, would not be able to do so without these skills.

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Scientists Create Method to Map Vast Unknown Territory of Long Non-coding RNAs (lncRNAs)

Scientists Create Method to Map Vast Unknown Territory of Long Non-coding RNAs (lncRNAs) | Amazing Science | Scoop.it

Researchers from the University of North Carolina at Chapel Hill have come up with a sequence motif-based strategy for sorting out functional similarities between long non-coding RNAs (lncRNAs). The authors of the study described their "sequence evaluation from k-mer representation" (SEEKR) method, which involves quantifying sequence k-mers to compare lncRNA and classify them functionally, in a paper published in Nature Genetics this week. They explained that SEEKR tallies and compares k-mer profiles, tallying k-mers of a given length in each lncRNA and normalizing these counts with insights about the lncRNA's overall length.

 

"We found that lncRNAs of related function often had similar k-mer profiles despite lacking linear homology, and that k-mer profiles correlated with protein binding to lncRNAs and with their sub-cellular localization," senior author J. Mauro Calabrese, a pharmacology researcher at UNC Chapel Hill's Lineberger Comprehensive Cancer Center, and his colleagues wrote.

 

Using this strategy, the team profiled and compared k-mer patterns in 161 lncRNAs known for their conservation in mice and humans, uncovering new and known functional similarities between lncRNAs. It also began clustering human and mouse lncRNAs into k-mer-based "communities" in an effort to understand their functions in relation to their cellular localization and other features. The investigators also used SEEKR — in combination with a "transposable element to test RNA's effect on transcription in cis," or TETRIS assay — to search for lncRNAs with regulatory functions similar to that attributed to Xist, a lncRNA with a documented role in cis-repression of gene expression. In doing so, they picked up a cis-repressive function for another lncRNA called Kcnq1ot1, despite pronounced differences between Xist and Kcnq1ot1 at the linear sequence level.

 

"SEEKR detected significant similarity between the cis-repressive Kcnq1ot1 and Xist lncRNAs where none was found by conventional alignment algorithms," the authors wrote. "We conclude that lncRNAs of related function can have related k-mer profiles even if they lack linear sequence similarity." Likewise, the researchers saw signs that still other lncRNAs — including NEAT1 and MALAT1 — may share previously unappreciated similarities with human and mouse versions of Xist. The repressive activity was more pronounced in lncRNAs with k-mers that were closer to Xist, they reported.

 

The team noted that most lncRNAs are not fully characterized functionally or mechanistically, although thousands have been identified in the human genome, encouraging the group to pursue a method for systematically assessing lncRNA functions.

"A major roadblock to progress remains the inability to detect recurrent relationships between lncRNA sequence and function," the authors wrote, explaining that "[a]n understanding of analogous relationships in proteins has enabled the classification of protein families, functional domains, and mechanisms that, in turn, have led to discoveries that have improve the diagnosis and treatment of disease." Based on their results so far, the researchers concluded that SEEKR's k-mer-based classification "is a powerful approach to dete

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Genetic testing could pick out people at three-fold increased risk of bone marrow cancer

Genetic testing could pick out people at three-fold increased risk of bone marrow cancer | Amazing Science | Scoop.it

Assessing DNA for areas of the genome linked to cancer risk could pick out some people with a three-fold increased risk of blood cancer, a new study suggests. The research identified six new DNA regions linked to a higher risk of multiple myeloma, a cancer of white blood cells made in the bone marrow.

 

Together with previously identified areas of the genome, their findings explain part of the inherited risk of myeloma. The people classed as at highest risk based on the genetic information identified so far were at three times the risk of developing the disease as the average individual. Despite there being around 5,700 new cases of myeloma diagnosed in the UK each year, there is still relatively little known about its causes.

 

This study, which was largely funded by Myeloma UK, increases the understanding of the complex genetics that underpin the disease, and could explain why some individuals are more at risk of developing myeloma. In future, specific genes in the newly identified risk regions of the DNA could also be possible targets of new drugs to treat the disease.

 

The research was published in the journal Nature Communications (13 September 2018).

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Novel flying robot mimics rapid insect flight almost perfectly

Novel flying robot mimics rapid insect flight almost perfectly | Amazing Science | Scoop.it

A novel insect-inspired flying robot, developed by TU Delft researchers from the Micro Air Vehicle Laboratory (MAVLab), has been presented in Science (14 September 2018). Experiments with this first autonomous, free-flying and agile flapping-wing robot – carried out in collaboration with Wageningen University & Research – improved our understanding of how fruit flies control aggressive escape maneuvers. Apart from its further potential in insect flight research, the robot’s exceptional flight qualities open up new drone applications.

 

Flying animals both power and control flight by flapping their wings. This enables small natural flyers such as insects to hover close to a flower, but also to rapidly escape danger, which everyone has witnessed when trying to swat a fly.

 

Animal flight has always drawn the attention of biologists, who not only study their complex wing motion patterns and aerodynamics, but also their sensory and neuromotor systems during such agile maneuvers. Recently, flying animals have also become a source of inspiration for robotics researchers, who try to develop lightweight flying robots that are agile, power-efficient and even scalable to insect sizes.

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AI algorithm teaches a car to drive from scratch in 20 minutes

A pair of artificial intelligence Ph.Ds from Cambridge University are going all-in on machine learning as the foundation of autonomous cars. Their company, Wayve, has just released video of a kitted-out Renault Twizy teaching itself to follow a lane from scratch, over the course of about 20 minutes.

 

Wayve's Amar Shah and Alex Kendall believe there's been too much hand-engineering going on as people try to solve the self-driving car problem. "The missing piece of the self-driving puzzle is intelligent algorithms, not more sensors, rules and maps," says Shah, Wayve co-founder and CEO. "Humans have a fascinating ability to perform complex tasks in the real world, because our brains allow us to learn quickly and transfer knowledge across our many experiences. We want to give our vehicles better brains, not more hardware."

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A new hydrogen-rich compound may be a record-breaking superconductor

A new hydrogen-rich compound may be a record-breaking superconductor | Amazing Science | Scoop.it

Two studies report evidence of superconductivity — the transmission of electricity without resistance — at temperatures higher than seen before. The effect appears in compounds of lanthanum and hydrogen squeezed to extremely high pressures. All known superconductors must be chilled to function, which makes them difficult to use in real-world applications. If scientists found a superconductor that worked at room temperature, the material could be integrated into electronic devices and transmission wires, potentially saving vast amounts of energy currently lost to electrical resistance. So scientists are constantly on the lookout for higher-temperature superconductors.

 

The current record-holder, hydrogen sulfide, which also must be compressed, works below 203 kelvins, or about −70° Celsius. The new evidence for superconductivity is based on a dramatic drop in the resistance of the lanthanum-hydrogen compounds when cooled below a certain temperature.

 

One team of physicists found that their compound’s resistance plummeted at a temperature of 260 kelvins (−13° C), the temperature of a very cold winter day. The purported superconductivity occurred when the material had been crushed with almost 2 million times the pressure of Earth’s atmosphere by squeezing it between two diamonds. Some samples even showed signs of superconductivity at higher temperatures, up to 280 kelvins (about 7° C), physicist Russell Hemley of George Washington University in Washington, D.C., and colleagues report in a study posted online August 23, 2018 at arXiv.org. Hemley first reported signs of the compound’s superconductivity in May 2018 in Madrid at a symposium on superconductivity and pressure.

 

Another group found evidence of superconductivity in a lanthanum-hydrogen compound under chillier, but still record-breaking, conditions. The researchers crushed lanthanum and hydrogen in a diamond press to about 1.5 million times Earth’s atmospheric pressure. When cooled to about 215 kelvins (−58° C), the compound’s resistance falls sharply, physicist Mikhail Eremets of the Max Planck Institute for Chemistry in Mainz and colleagues report in a paper posted online August 21, 2018 at arXiv.org.

 

It’s not clear what the exact structures of the chemical compounds are and whether the two groups are studying identical materials. Differences between the two teams’ samples might explain the temperature discrepancy. By scattering X-rays from the compound, Hemley and colleagues showed that the material’s structure was consistent with LaH10, which contains 10 hydrogen atoms for every lanthanum atom. Hemley’s team had previously predicted that LaH10 would be superconducting at a relatively high temperature.

 

The results are “very exciting,” says theoretical chemist Eva Zurek of the University at Buffalo in New York. However, the studies are not conclusive: They have not been peer reviewed and do not yet show an essential hallmark of superconductivity called the Meissner effect, in which magnetic fields are expelled from the superconducting material (SN: 8/8/15, p. 12). But the results agree with the previous theoretical predictions made by Hemley and colleagues. So, Zurek says, “I would hope and suspect that this is indeed … correct.”

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Using AI to make cancer evolution more predictable

Using AI to make cancer evolution more predictable | Amazing Science | Scoop.it

A team of researchers affiliated with several institutions in the U.K. and one in the U.S. has developed a way to use artificial intelligence to predict how cancer might change and spread in patients. The results are published in Nature Methods.

 

Over many years of cancer research, scientists have discovered that tumors actually evolve, allowing them to change their form and the way they spread. Understanding how this evolutionary process works is considered by many in the field to be a key part of learning how to prevent it from happening. As part of this effort, scientists have collected tissue samples from patients hoping to find a pattern in how they change. But this method has proven to be difficult, because when tumors grow, they also tend to develop mutations that have no impact on their ability to spread. In this new effort, the researchers sought to add machine learning to the process in an effort to track evolutionary changes that are involved in spreading. They have named their new system Revolver.

 

The new application uses a machine learning algorithm to study mutation data and detect patterns. They fed their system data describing 768 tumors from 178 patients—each of whom had breast, kidney, bowel or lung cancer. The system sought mutation patterns between patients that appeared to be related to changes that allowed the tumor to spread. Next, they applied what the system had learned to new patients as a way to assess the state of newly developing tumors—it was correctly identified gene mutations in 95 colorectal patients who had mutations that had been previously identified as drivers of evolution in breast, kidney and lung cancers.

 

The researchers note that Revolver is just one of the first steps toward developing computer-based tools to better predict how tumors will evolve—such tools should make it easier for doctors to formulate the best treatment plan for a given patient, hopefully, improving their prognosis.

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The true driver mutations of cancer are almost always common to all metastases in an individual

The true driver mutations of cancer are almost always common to all metastases in an individual | Amazing Science | Scoop.it

Scientists have arrived at a key understanding about how cancers in individual patients spread, or metastasize, a study from the Stanford University School of Medicine and other collaborating institutions reports. The study found that mutations that drive cancer growth are common among metastases in a single patient.

 

Most cancer-related deaths are caused by metastases, or secondary tumors in distant locations of the body that have spread away from the original, primary tumor. While primary tumors can often be surgically removed, metastatic tumors typically require treatment such as standard chemotherapy or targeted therapy. The success of such new targeted therapies depends on the presence of a specific mutation in all cancer cells, in particular in metastatic tumors.

 

Until now, most studies that aimed to decode the genetic variability, or heterogeneity, of cancers focused mainly on primary tumors. And while that information is still extremely valuable, it leaves much of the story untold; cancer cells are notorious for their ability to change, evolve and evade treatments, particularly as they spread in the body.

 

“We took samples from multiple untreated metastases of each patient, and we observed a mix of overlapping and differing driver mutations,” said Johannes Reiter, PhD, an instructor of radiology at Stanford. “But through computational analyses, we inferred that the driver mutations that were most likely to contribute to cancer development were shared among all metastases in each patient.”

 

A tumor comprised of billions of cells is riddled with genetic mutations; cancer cells and normal cells acquire multiple mutations as they divide. Identifying the driver mutations that significantly contribute to cancer development is critical to precision oncology, in which doctors aim to treat a patient’s cancer based on its genetic composition.

 

“Doctors might take a sample of the primary tumor and find some mutation — call it mutation X — in a driver gene and then treat it with a drug that targets that driver gene to specifically kill all cells that have mutation X,” Reiter said. “But what if that particular mutation is only present in some of the metastases of the patient?” Only the metastases comprised of cells with mutation X would respond to treatment and shrink or go extinct; those without mutation X would continue to grow. In the end, the doctor wouldn’t see a remission of the patient’s cancer if driver mutations were different across its metastases. “So that’s why it’s very important for us to know whether or not the driver gene mutations are the same across all metastases of the patient,” Reiter said.

 

The paper was published Sept. 7, 2018 in Science

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The role of random nanostructures for the omnidirectional anti-reflection properties of the glasswing butterfly

The role of random nanostructures for the omnidirectional anti-reflection properties of the glasswing butterfly | Amazing Science | Scoop.it

Glasswing butterflies develop nanostructures on their wings that actually give them “anti-reflective” properties. This allows them to reduce the amount of light bouncing their wings & remain transparent in a terrestrial environment, something few animals on the planet can do.

 

The glasswing butterfly (Greta oto) has, as its name suggests, transparent wings with remarkable low haze and reflectance over the whole visible spectral range even for large view angles of 80°. This omnidirectional anti-reflection behaviour is caused by small nanopillars covering the transparent regions of its wings. In difference to other anti-reflection coatings found in nature, these pillars are irregularly arranged and feature a random height and width distribution. Scientists now simulate the optical properties with the effective medium theory and transfer matrix method and show that the random height distribution of pillars significantly reduces the reflection not only for normal incidence but also for high view angles.

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New Texas supercomputer to push the frontiers of science

New Texas supercomputer to push the frontiers of science | Amazing Science | Scoop.it

The National Science Foundation (NSF) announced today that it has awarded $60 million to the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for the acquisition and deployment of a new supercomputer that will be the fastest at any U.S. university and among the most powerful in the world.

 

The new system, known as Frontera (Spanish for "frontier"), will begin operations in 2019. It will allow the nation's academic researchers to make important discoveries in all fields of science, from astrophysics to zoology, and further establishes The University of Texas at Austin's leadership in advanced computing.

 

"Supercomputers — like telescopes for astronomy or particle accelerators for physics — are essential research instruments that are needed to answer questions that can't be explored in the lab or in the field," said Dan Stanzione, TACC executive director. "Our previous systems have enabled major discoveries, from the confirmation of gravitational wave detections by the Laser Interferometer Gravitational-wave Observatory to the development of artificial-intelligence-enabled tumor detection systems. Frontera will help science and engineering advance even further."

 

"For over three decades, NSF has been a leader in providing the computing resources our nation's researchers need to accelerate innovation," said NSF Director France Córdova. "Keeping the U.S. at the forefront of advanced computing capabilities and providing researchers across the country access to those resources are key elements in maintaining our status as a global leader in research and education. This award is an investment in the entire U.S. research ecosystem that will enable leap-ahead discoveries."

 

Frontera is the latest in a string of successful awards and deployments by TACC with support from NSF. Since 2006, TACC has built and operated three supercomputers that debuted in the Top 10 most powerful systems in the world: Ranger (2008), Stampede1 (2012) and Stampede2 (2017). Three other systems debuted in the Top 25.

 

If completed today, Frontera would be the fifth most powerful system in the world, the third fastest in the U.S. and the largest at any university. For comparison, Frontera will be about twice as powerful as Stampede2 (currently the fastest university supercomputer) and 70 times as fast as Ranger, which operated until 2013. To match what Frontera will compute in just one second, a person would have to perform one calculation every second for about a billion years.

 

Anticipated early projects on Frontera include analyses of particle collisions from the Large Hadron Collider, global climate modeling, improved hurricane forecasting and multi-messenger astronomy.

The primary computing system will be provided by Dell EMC and powered by Intel processors. Data Direct Networks will contribute the primary storage system, and Mellanox will provide the high-performance interconnect for the machine. NVIDIA, GRC (Green Revolution Cooling), CoolIT Systems, and the cloud providers Amazon, Google, and Microsoft will also have roles in the project.

"The new Frontera systems represents the next phase in the long-term relationship between TACC and Dell EMC, focused on applying the latest technical innovation to truly enable human potential," said Thierry Pellegrino, vice president of Dell EMC High Performance Computing. "The substantial power and scale of this new system will help researchers from Austin and across the U.S. harness the power of technology to spawn new discoveries and advancements in science and technology for years to come."

 

"Accelerating scientific discovery lies at the foundation of the TACC's mission, and enabling technologies to advance these discoveries and innovations is a key focus for Intel," said Patricia Damkroger, Vice President in Intel's Data Center Group and General Manager, Extreme Computing Group. "We are proud that the close partnership we have built with TACC will continue with TACC's selection of next-generation Intel Xeon Scalable processors as the compute engine for their flagship Frontera system."

 

Faculty at the Institute for Computational Engineering and Sciences (ICES) at UT Austin will lead the world-class science applications and technology team, with partners from the California Institute of Technology, Cornell University, Princeton University, Stanford University, the University of Chicago, the University of Utah and the University of California, Davis.

 

Experienced technologists and operations partners from the sites above as well as The Ohio State University, the Georgia Institute of Technology and Texas A&M University will ensure the system runs effectively in all areas, including security, user engagement and workforce development.

 
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Chemicals found in tiny rocks from Australia likely remains of some of Earth’s first life forms, study finds

Chemicals found in tiny rocks from Australia likely remains of some of Earth’s first life forms, study finds | Amazing Science | Scoop.it

Chemicals found in 3.4 billion-year-old rocks have confirmed them as contenders for the title of oldest evidence of life on Earth.

Discovered in Western Australia back in 2013, the Strelley Pool “microfossils” are thought to be all that remains of ancient bacteria. But the passage of time takes its toll on all fossils, especially microscopic ones. This means any remains that are discovered are the subject of enormous debate in the scientific community.

 

In their latest study, a team of scientists used the chemical traces left on the miniscule structures found at Strelley and compared them with the chemical signatures of modern-day bacteria.

They also used more recent microfossil evidence from 1.9 billion year-old Canadian rock formations as an additional comparison, and found that the characteristics of each were roughly the same.

“We demonstrate that the elemental and molecular characteristics of these 3.4 billion year-old microfossils are consistent with biological remains, slightly degraded by fossilisation processes,” said Dr Julien Alleon, a Massachusetts Institute of Technology scientist who led the study. “This effectively supports the biological origin of the Strelley Pool microfossils.”

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Can Immunotherapy Succeed in Glioblastoma?

Can Immunotherapy Succeed in Glioblastoma? | Amazing Science | Scoop.it
Researchers are hopeful that, for the deadly brain cancer glioblastoma, immunotherapy might succeed where other therapies have not. As this Cancer Currents post reports, different immunotherapy approaches are being tested in clinical trials.

 

Cancer treatments that work by engaging the immune systemto attack tumors have proven to be effective against a growing number of cancers. One notable exception thus far, however, has been brain cancer, including glioblastoma, the most common type of brain cancer in adults.

 

Despite continued efforts over several decades to develop new therapies for glioblastoma, none has appreciably improved how long patients live. Most people with this type of brain cancer, in fact, survive for less than 2 years.

 

Researchers who study glioblastoma have been hopeful that immunotherapy might be able to succeed where other therapies have not. And in laboratory studies and human clinical trials, they are leaving no immunotherapy stone unturned. Unfortunately, several immune-based treatments that looked highly promising in early-phase studies of patients with glioblastoma have not panned out in larger, phase 3 clinical trials. But even those failures have a silver lining, said Michael Lim, M.D., who directs the Brain Tumor Immunotherapy program at the Johns Hopkins University Sidney Kimmel Comprehensive Cancer Center.

 

“Just the fact that we have had some phase 3 [immunotherapy] trials in glioblastoma, where for years we had a hard time getting past phase 2 trials, is an encouraging sign,” Dr. Lim said.

There is undoubtedly optimism among researchers about the prospects for immunotherapy as an effective treatment for glioblastoma. At the same time, through their work in the lab and in the clinic, researchers are exploring a critical question: how to overcome the unique and daunting challenges presented by the brain and of glioblastoma itself.

 

“We’re talking about a disease that has been one of the hardest to treat in the history of oncology,” said Mark Gilbert, M.D., director of the Neuro-Oncology Branch in NCI’s Center for Cancer Research. And trying to develop and test immune-based treatments for glioblastoma, Dr. Gilbert continued, “is a whole new realm.”

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