WORLD’S LARGEST NATURAL SOUND LIBRARY NOW ONLINE

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The Macaulay Library, with over 150,000 recordings of 9,000 species is now digitised and has been uploaded to an online searchable database.

The library, housed at Cornell University’s Lab of Ornithology, has made available over ten terabytes of recordings, with a runtime of 7513 hours of natural sounds.

The collection, which began in 1929 has taken researchers dozens of years to accumulate. It currently holds recordings to a massive three-quarters of the world’s entire bird species, but it’s not all chirps and squawks, there’s also a decent helping of whale songs, insects, bears, elephants, primates and just about every other critter or creepy crawley that roams the earth.

The collection’s curator Greg Budney describes the archives as revolutionary, in terms of the speed and the breadth of material that is now accessible online.

“This is one of the greatest research and conservation resources at the Cornell Lab,” said Budney. “And through its digitization we’ve swung the doors open on it in a way that wasn’t possible 10 or 20 years ago.”

“Our audio collection is the largest and the oldest in the world,” explained Macaulay Library director Mike Webster. “Now, it’s also the most accessible. We’re working to improve search functions and create tools people can use to collect recordings and upload them directly to the archive. Our goal is to make the Macaulay Library as useful as possible for the broadest audience possible.”

Now the team has digitised its massive archive, it’s focusing on collecting new material from amateur and professional recordists from around the world.

The sounds are not only used by sound designers and filmmakers, but also by researchers, museums, or anyone interested in the sounds of nature.

“Plus, it’s just plain fun to listen to these sounds,” explained Bundy. “Have you heard the sound of a walrus underwater? It’s an amazing sound.” 

*UPDATE*

We had previously stated the library was free to use, but that seems not to be the case – rather, it’s ‘free to listen’. Licensing for commercial and non-commercial use is available, however it requires submitting an online purchase order, which may have fees associated with it (in other words, not free).

You can access the library now at macaulaylibrary.org.

Sound Recordists Chris Watson (image: lists/uk)

Check out some of the fun sounds found at the library:

• Earliest recording: Cornell Lab founder Arthur Allen was a pioneer in sound recording. On a spring day in 1929 he recorded this Song Sparrow sounding much as they do today.
• Best candidate to appear on a John Coltrane record: The indri, a lemur with a voice that is part moan, part jazz clarinet
• Most spines tingled: The incomparable voice of a Common Loon on an Adirondacks lake in 1992
• Most erratic construction project: the staccato hammering sounds of a walrus under water
• Most likely to be mistaken for aliens arriving: Birds-of-paradise make some amazing sounds – here’s the UFO-sound of a Curl-crested Manucode in New Guinea

ORIGINAL: Video and Film Maker

Acoustic tweezers manipulate cells with sound waves

An illustration of the surface acoustic wave generators, with the generated 3-D trapping nodes. The inset indicates a single particle within a 3-D trapping node, which can be manipulated independently along x, y, or z axes.

Technique could enable 3-D printing of cellular structures for tissue engineering.

Engineers at MIT, Penn State University, and Carnegie Mellon University have devised a way to manipulate cells in three dimensions using sound waves. These “acoustic tweezers” could make possible 3-D printing of cell structures for tissue engineering and other applications, the researchers say.

Designing tissue implants that can be used to treat human disease requires precisely recreating the natural tissue architecture, but so far it has proven difficult to develop a single method that can achieve that while keeping cells viable and functional.

“The results presented in this paper provide a unique pathway to manipulate biological cells accurately and in three dimensions, without the need for any invasive contact, tagging, or biochemical labeling,” says Subra Suresh, president of Carnegie Mellon and former dean of engineering at MIT. “This approach could lead to new possibilities for research and applications in such areas as regenerative medicine, neuroscience, tissue engineering, biomanufacturing, and cancer metastasis.”

Suresh, Ming Dao, a principal research scientist in MIT’s Department of Materials Science and Engineering, and Tony Jun Huang, a professor of engineering science and mechanics at Penn State, are senior authors of a paper describing the device, published the week of Jan. 25. in the Proceedings of the National Academy of Sciences.

The paper’s lead author is Penn State graduate student Feng Guo. The team also includes Penn State researchers Zhangming Mao, Yuchao Chen, James Lata, Peng Li, Liqiang Ren, Jiayang Liu, Zhiwei Xie, and Jian Yang.

3-D control

The new acoustic tweezers are based on a microfluidic device that the researchers previously developed to manipulate cells in two dimensions. This device produces two acoustic standing waves, which are waves with a constant height. Where the two waves meet, they create a “pressure node” that can trap single cells. By altering the wavelength and another wave property known as the phase, the researchers can move the node and the cell trapped within it.

The research team previously used a similar approach to separate cancer cells from healthy cells, which could be useful for detecting rare tumor cells in a patient’s bloodstream and predicting whether the tumor will spread.

In the new study, the researchers added a third dimension of control: Once the cells are trapped in a horizontal plane, they can be moved up and down by altering the acoustic waves’ power, that is, the rate at which sound energy is emitted. Boosting the power allows the researchers to lift the cells from the surface in a type of “acoustic levitation,” then place them in a specific location, Dao says.

The researchers also developed equations that allow them to accurately predict how changes in the wavelength, phase, and acoustic power will affect cells’ positions.

“We now have a good idea of what to expect and how to control the 3-D positioning of the acoustic waves and the pressure nodes, enabling validation of the method as well as system optimization,” Dao says.

“Innovative approach”

In this study, the researchers demonstrated their device on polystyrene particles as well as mouse fibroblast cells. They were able to move the cells, one at a time, into specific positions on a surface and create patterns. They could also stack cells on top of each other.

“This is an exceptionally innovative approach of manipulating particles and single cells in 3-D in fluids,” says Taher Saif, a professor of mechanical science and engineering at the University of Illinois at Urbana-Champaign, who was not part of the research team. “Since acoustic energy is used for this manipulation, the approach is noninvasive and the cells maintain their viability. Overall, the method presented will be of significant interest for a broad community, from biologists to bioengineers.”

The researchers have filed for a patent on the technology and plan to continue developing it for tissue engineering and other applications.

ORIGINAL: MIT News

Anne Trafton | MIT News Office 

January 25, 2016

Here’s What Developers Are Doing with Google’s AI Brain

Researchers outside Google are testing the software that the company uses to add artificial intelligence to many of its products.

WHY IT MATTERS

Tech companies are racing to set the standard for machine learning, and to attract technical talent.

Jeff Dean speaks at a Google event in 2007. Credit: Photo by Niall Kennedy / CC BY-NC 2.0

An artificial intelligence engine that Google uses in many of its products, and that it made freely available last month, is now being used by others to perform some neat tricks, including 

• translating English into Chinese, 
• reading handwritten text, and 
• even generating original artwork.

The AI software, called Tensor Flow, provides a straightforward way for users to train computers to perform tasks by feeding them large amounts of data. The software incorporates various methods for efficiently building and training simulated “deep learning” neural networks across different computer hardware.

Deep learning is an extremely effective technique for training computers to recognize patterns in images or audio, enabling machines to perform with human-like competence useful tasks such as recognizing faces or objects in images. Recently, deep learning also has shown significant promise for parsing natural language, by enabling machines to respond to spoken or written queries in meaningful ways.

Speaking at the Neural Information Processing Society (NIPS) conference in Montreal this week, Jeff Dean, the computer scientist at Google who leads the Tensor Flow effort, said that the software is being used for a growing number of experimental projects outside the company.

These include software that generates captions for images and code that translates the documentation for Tensor Flow into Chinese. Another project uses Tensor Flow to generate artificial artwork. “It’s still pretty early,” Dean said after the talk. “People are trying to understand what it’s best at.”

Tensor Flow grew out of a project at Google, called Google Brain, aimed at applying various kinds of neural network machine learning to products and services across the company. The reach of Google Brain has grown dramatically in recent years. Dean said that the number of projects at Google that involve Google Brain has grown from a handful in early 2014 to more than 600 today.

Most recently, the Google Brain helped develop Smart Reply, a system that automatically recommends a quick response to messages in Gmail after it scans the text of an incoming message. The neural network technique used to develop Smart Reply was presented by Google researchers at the NIPS conference last year.

Dean expects deep learning and machine learning to have a similar impact on many other companies. “There is a vast array of ways in which machine learning is influencing lots of different products and industries,” he said. For example, the technique is being tested in many industries that try to make predictions from large amounts of data, ranging from retail to insurance.

Google was able to give away the code for Tensor Flow because the data it owns is a far more valuable asset for building a powerful AI engine. The company hopes that the open-source code will help it establish itself as a leader in machine learning and foster relationships with collaborators and future employees. Tensor Flow “gives us a common language to speak, in some sense,” Dean said. “We get benefits from having people we hire who have been using Tensor Flow. It’s not like it’s completely altruistic.”

A neural network consists of layers of virtual neurons that fire in a cascade in response to input. A network “learns” as the sensitivity of these neurons is tuned to match particular input and output, and having many layers makes it possible to recognize more abstract features, such as a face in a photograph.

Tensor Flow is now one of several open-source deep learning software libraries, and its performance currently lags behind some other libraries for certain tasks. However, it is designed to be easy to use, and it can easily be ported between different hardware. And Dean says his team is hard at work trying to improve its performance.

In the race to dominate machine learning and attract the best talent, however, other companies may release competing AI engines of their own.

ORIGINAL: Technology Review

By Will Knight

December 8, 2015

For First Time, Researchers Demonstrate Heat and Sound Are Magnetic

 Photo: Ohio State University

Earlier this month, we reported on research demonstrating that heat propagates as a wave through graphene rather than as vibrations of atoms the way it does in 3-D materials. In 3-D materials, the collective state of those vibrating atoms is known as phonons.

For the first time, researchers at Ohio State University (OSU) have demonstrated that acoustic phonons, which can carry both heat and sound, have magnetic properties that allow them to be manipulated with magnetism.

In research published in the journal Nature Materials, the OSU researchers applied a magnetic field equivalent to that inside a magnetic resonance imaging (MRI) device (in this case, the magnet was reported to be fairly powerful at seven Tesla). They discovered that they could reduce the amount of heat flowing through a semiconductor by 12 percent.

“This adds a new dimension to our understanding of acoustic waves,” said Joseph Heremans, professor of mechanical engineering at Ohio State, in a press release. “We’ve shown that we can steer heat magnetically. With a strong enough magnetic field, we should be able to steer sound waves, too.”

Before anyone starts thinking about the discovery’s applicability to heat management in computers, they should keep in mind that the semiconductor had to be kept at temperatures very close to absolute zero (specifically, -268 degrees Celsius) in order for the researchers to measure the movements of the phonons.

In fact, it was the complexity of taking the measurements that had prevented researchers from recognizing the magnetic properties of phonons previously. In order to take thermal measurements at such a low temperature, Hyungyu Jin, a postdoctoral researcher and lead author of the study, used the semiconductor indium antimonide and shaped it into a lopsided tuning fork in which one arm was 4 millimeters wide and the other was 1 mm wide. Then he placed a heater at the base of each arm.

At normal temperatures, the ability of the material to transfer heat would be solely dependent on the kind of atoms in the material. But near absolute zero, the ability of the material to transfer heat can be determined by the physical size of the material. In this case, the difference in the sizes of the fork arms was significant. Phonons more easily filled the wider arm.

“Imagine that the tuning fork is a track, and the phonons flowing up from the base are runners on the track,” explained Heremans in the press release. “The runners who take the narrow side of the fork barely have enough room to squeeze through, and they keep bumping into the walls of the track, which slows them down. The runners who take the wider track can run faster, because they have lots of room.”

Eventually they all end up at their respective finish lines. But the track’s geometry determines just how quickly.

With this understanding, Jin was able to compare the temperature changes in the two fork arms. He first took the measurements without a magnet and then with one. With the magnet on, the heat flow through the larger arm slowed down by 12 percent.

Now that the researchers have measured magnetism’s effect on heat, they want to move on to see if they can use it to deflect sound waves.

Learn More Ohio State Universitygrapheneheatmagnetismphononssemiconductorssound waves

ORIGINAL: Spectrum
By Dexter Johnson
24 Mar 2015