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Original author: 
John Timmer

elliottzone

One of the problems with cognitive and behavioral research is getting a good cross-section of the general population. Although they're convenient to work with, a couple hundred college students rarely represent the full diversity of human capability and behavior, yet that's exactly what many studies rely on. But a brain-training game may now provide access to data on scales that behavioral scientists probably never dreamed of. With a user base of over 35 million, the data obtained through the game could help us tease out very subtle effects. But as a start, a team of researchers have focused on some simpler questions: how aging and alcohol affect our ability to learn.

The software is less a game itself than a game and survey platform. Developed by a company called Lumosity, it's available on mobile platforms and through a Web interface. The platform can run a variety of games (a typical one asks users to answer math questions that appear in raindrops before they hit the ground), all with an emphasis on brain training. A few games are available for free and users can pay to get access to more advanced ones.

The scientific literature on brain training games is a bit mixed, and there's some controversy about whether the games improve mental function in general, or only those specific areas of cognition that the game focuses on. Lumosity clearly argues for the former and one of its employees pointed Ars to a number of studies that he felt validate the company's approach. What's not in doubt, however, is that it has a huge user base with over 35 million registered users. And because the Lumosity platform is flexible, it has been able to get basic demographic information from many of those users; they and others have also filled out personality profiles and other assessments.

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Original author: 
Allie Wilkinson

Lynn Tomlinson

Cooperation occurs when we act on behalf of a common benefit, often at personal cost. Everyone would be better off if an entire group cooperates, but some individual members can do better if they go it alone, so self-interest undermines cooperation. A new study indicates that your reputation—in terms of whether people are aware that you're cooperating—plays a pivotal role in your decision to cooperate.

Studies on the evolution of cooperation, or how cooperation can emerge and persist, use the Prisoner’s Dilemma as the standard example to demonstrate why people may choose not to cooperate. In the Prisoner’s Dilemma, two men are arrested and held in separate cells. Due to a lack of evidence, the prosecution plans to sentence each man to year in prison on a lesser charge. If either suspect testifies against his partner, he will go free, while his partner will be sentenced to three years in prison; if both men testify against each other, then they will each serve two years. Each man is better off if he cooperates.

The Prisoner’s Dilemma is an example of direct reciprocity, where two individuals affect one another's fate. But cooperation can also be based on indirect reciprocity, which is centered on repeated encounters between a group of individuals. In a sense, it’s the karmic approach—the belief that your good deeds toward others will come full-circle, and someone will eventually scratch your back.

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Original author: 
Sean Gallagher


A frame of Timelapse's view of the growth of Las Vegas, Nevada.

Google, USGS

This story has been updated with additional information and corrections provided by Google after the interview.

In May, Google unveiled Earth Engine, a set of technologies and services that combine Google's existing global mapping capabilities with decades of historical satellite data from both NASA and the US Geological Survey (USGS). One of the first products emerging from Earth Engine is Timelapse—a Web-based view of changes on the Earth's surface over the past three decades, published in collaboration with Time magazine.

The "Global Timelapse" images are also viewable through the Earth Engine site, which allows you to pan and zoom to any location on the planet and watch 30 years of change, thanks to 66 million streaming video tiles. The result is "an incontrovertible description of what's happened on our planet due to urban growth, climate change, et cetera," said Google Vice President of Research and Special Initiatives Alfred Spector.

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Original author: 
Matthew Francis


Nobody knows what the mathematician Rev. Thomas Bayes looked like, but this is the picture everyone uses. The equation is Bayes' theorem.

Nate Silver, baseball statistician turned political analyst, gained a lot of attention during the 2012 United States elections when he successfully predicted the outcome of the presidential vote in all 50 states. The reason for his success was a statistical method called Bayesian inference, a powerful technique that builds on prior knowledge to estimate the probability of a given event happening.

Bayesian inference grew out of Bayes' theorem, a mathematical result from English clergyman Thomas Bayes, published two years after his death in 1761. In honor of the 250th anniversary of this publication, Bradley Efron examined the question of why Bayes' theorem is not more widely used—and why its use remains controversial among many scientists and statisticians. As he pointed out, the problem lies with blind use of the theorem, in cases where prior knowledge is unavailable or unreliable.

As is often the case, the theorem ascribed to Bayes predates him, and Bayesian inference is more general than what the good reverend worked out in his spare time. However, Bayes' posthumous paper was an important step in the development of probability theory, and so we'll stick with using his name.

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Original author: 
John Timmer

FirasMT

In the past few years, there have been a regular series of announcements about devices that cloak something in space. These typically bend light around the cloak so that it comes out behind the object looking as if it had never shifted at all. In contrast, there's just been a single description of a temporal cloaking device, something that hides an event in time. The device works because in some media different frequencies of light move at different speeds. With the right combination of frequency shifts, it's possible to create and then re-seal a break in a light beam.

But that particular cloak could only create breaks in the light beam that lasted picoseconds. Basically, you couldn't hide all that much using it. Now, researchers have taken the same general approach and used it to hide signals in a beam of light sent through an optical fiber. When the cloak is in operation, the signals largely disappear. In this case the cloak can hide nearly half of the total bandwidth of the light, resulting in a hidden transmission rate of 12.7 Gigabits per second.

The work started with the Talbot effect in mind, in which a diffraction grating causes repeated images of the grating to appear at set distances away from it. The cloaking device relies on the converse of this. At other distances, the light intensity drops to zero. The key trick is to convert the Talbot effect from something that happens in space to something that happens in time.

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Original author: 
John Timmer


The D-Wave Two.

D-Wave

D-Wave's quantum optimizer has found a new customer in the form of a partnership created by Google, NASA, and a consortium of research universities. The group is forming what it's calling the Quantum Artificial Intelligence Lab and will locate the computer at NASA's Ames Research Center. Academics will get involved via the Universities Space Research Association.

Although the D-Wave Two isn't a true quantum computer in the sense the term is typically used, D-Wave's system uses quantum effects to solve computational problems in a way that can be faster than traditional computers. How much faster? We just covered some results that indicated a certain class of problems may be sped up by as much as 10,000 times. Those algorithms are typically used in what's termed machine learning. And machine learning gets mentioned several times in Google's announcement of the new hardware.

Machine learning is typically used to allow computers to classify features, like whether or not an e-mail is spam (to use Google's example) or whether or not an image contains a specific feature, like a cat. You simply feed a machine learning system enough known images with and without cats and it will identify features that are shared among the cat set. When you feed it unknown images, it can determine whether enough of those features are present and make an accurate guess as to whether there's a cat in it. In more serious applications machine learning has been used to identify patterns of brain activity that are associated with different visual inputs, like viewing different letters.

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Original author: 
John Timmer

Stockton.edu

How do ethics and the free market interact? As the authors of a new paper on the topic point out, the answer is often complicated. In the past, Western economies had vigorous markets for things we now consider entirely unethical, like slaves and Papal forgiveness for sins. Ending those practices took long and bloody struggles. But was this because the market simply reflects the ethics of the day, or does engaging in a market alter people's perception of what's ethical?

To find out, the authors of the paper set up a market for an item that is ethically controversial: the lives of lab animals. They found that, for most people, keeping a mouse alive, even at someone else's cost, is only worth a limited amount of money. But that amount goes down dramatically once market-based buying and selling is involved.

The research was done at the University of Bonn, which appears to have a biology department that includes researchers who study mouse genetics. As Mendel told us, genes are inherited independently. So as these researchers are breeding mice to get a specific combination of genes, they'll inevitably get mice that have the wrong combination. Since proper mouse care is expensive and lab mice typically live a couple of years, it's standard procedure to euthanize these unneeded mice.

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Original author: 
John Timmer

Arthur Toga, University of California, Los Angeles

In 1992, at the age of 70, a US citizen suffered a severe case of viral encephalitis, a swelling of the brain caused by infection. After he recovered two years later, he appeared completely average based on an IQ test (indeed, he scored 103). Yet in other ways, he was completely different. Several decades of his past life were wiped completely from his brain. His only accessible memories came from his 30s, and from the point of his illness to his death, he would never form another memory that he was aware of.

But this severe case of what appears to be total amnesia doesn't mean he had no memory as we commonly understand it. The patient, called E.P., was studied intensely using a battery of tests for more than a decade, with researchers giving him tests during hundreds of sessions. After his death, his brain was given for further study. With the analysis of the brain complete, the people who studied him have taken the opportunity to publish a review of all his complex memory problems.

Aside from memory, there were only a few obvious problems with E.P. Most of his senses were normal except smell, which was wiped out (a condition called anosmia). His vision was perfectly fine, but he had two specific problems interpreting what he saw. One was a limited ability to discriminate between faces, and the other was difficulty in determining whether a line drawing represented an object that's physically impossible (think M. C. Escher drawings).

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Original author: 
WIRED UK


Sunrise over a wheat field.

The Knowles Gallery

Researchers have managed to turn indigestible cellulose into starch, a process that could render billions of tons of agricultural waste into food and fuel.

Plants grow more than 160 billion tons of cellulose—the material that makes up the walls of plant cells—every year, but only a tiny fraction of that is useful to humans in the crops we grow. This is frustrating, as cellulose is made up of glucose chains that are almost, but not quite, the same as those that make up the starch that constitutes 20 to 40 percent of most peoples' daily calorie intake.

With the world's population forecast to reach nine billion by 2050, working out how to alter cellulose glucose into something more practical could be vital for preventing starvation. There's also an extra benefit in that some could be used for biofuels.

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Original author: 
Akshat Rathi

U Penn

In recent years, massive open online courses (MOOCs), through the likes of Coursera, have attracted hundreds of thousands of students from across the world. Many teachers are using a "flipped" classroom model, where students take lectures through videos at their convenience and spend the time in class delving into issues they don't understand.

But are they really improving learning? The evidence is not fully convincing. A 2010 meta-analysis of the literature on online teaching by the US Department of Education revealed that there are only "modest benefits" to online learning compared to classroom learning, but more rigorous studies were needed. After all, ease of access to the learning material comes with a bundle of distractions only a single click away. Not surprisingly, studies have shown that students suffer from attention lapses when learning through videos.

Given those findings, an improvement in students' attentiveness is bound to pay significant dividends. To that end, Karl Szpunar, a cognitive psychologist at Harvard University, might have a rather simple solution to rein in distractions, one that focuses attention in real-world classrooms: intersperse pop quizzes into the online lectures.

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