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John Timmer

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Flickr user: Andreas Poike

High-frequency trading is the practice where automated systems search for minor differences in price of stocks that can be exploited for small financial gains. Executed often enough and with a high enough investment, they can lead to serious profits for the investment firms that have the wherewithal to run these systems. The systems trade with minimal human supervision, however, and have been blamed for a number of unusually violent swings that have taken place in the stock market.

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Flickr user: Brent Moore

Fake masculinity on demand. At first, this seems like a case of neat science. Many species of cephalopods have the ability to change coloration on demand, and some researchers have found a species of squid where the females have three stripes running down their mantles. The interesting bit is that they use two different mechanisms for controlling the color changes of these stripes. The weird bit is why they change color: the authors suspect that the stripes can make a female look like it's a male. That can keep males from trying to mate with it, which may be helpful if the female already has mated.

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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: 
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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A cartoon showing spikes of activity traveling among neurons.

UC Berkeley

Computing hardware is composed of a series of binary switches; they're either on or off. The other piece of computational hardware we're familiar with, the brain, doesn't work anything like that. Rather than being on or off, individual neurons exhibit brief spikes of activity, and encode information in the pattern and timing of these spikes. The differences between the two have made it difficult to model neurons using computer hardware. In fact, the recent, successful generation of a flexible neural system required that each neuron be modeled separately in software in order to get the sort of spiking behavior real neurons display.

But researchers may have figured out a way to create a chip that spikes. The people at HP labs who have been working on memristors have figured out a combination of memristors and capacitors that can create a spiking output pattern. Although these spikes appear to be more regular than the ones produced by actual neurons, it might be possible to create versions that are a bit more variable than this one. And, more significantly, it should be possible to fabricate them in large numbers, possibly right on a silicon chip.

The key to making the devices is something called a Mott insulator. These are materials that would normally be able to conduct electricity, but are unable to because of interactions among their electrons. Critically, these interactions weaken with elevated temperatures. So, by heating a Mott insulator, it's possible to turn it into a conductor. In the case of the material used here, NbO2, the heat is supplied by resistance itself. By applying a voltage to the NbO2 in the device, it becomes a resistor, heats up, and, when it reaches a critical temperature, turns into a conductor, allowing current to flow through. But, given the chance to cool off, the device will return to its resistive state. Formally, this behavior is described as a memristor.

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Giant viruses being built inside an infected cell.

Didier Raoult

In July of last year, researchers in France described a rather disturbing example of what could happen if you're not careful about cleaning your contact lenses. A 17-year-old patient had been wearing monthly lenses well past their expiration date, and rinsing them with a cleaning solution she'd diluted with tap water. The end result was an eye infection. Luckily, a bit of care managed to clear it up.

In the meantime, the people who treated her dumped some of the solution out of her contact lens case and started trying to culture any parasites that would grow out of it. In the end, they got an entire ecosystem—all contained inside a single strain of amoeba. Among the parasites-within-parasites were a giant virus, a virus that targets that virus, and a mobile piece of DNA that can end up inserting into either of them.

When they first grew the amoeba from the contact lens cleaning solution, they found it contained two species of bacteria living inside it. But they also found a giant virus, which they called Lentille virus. These viruses have been known for a while, and they tend to affect amoebas, so this wasn't a huge surprise.

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The filaments created by a slime mold, along with the slime left behind on paths it discards.

SUNY.edu

Is it possible to know where you've been when you don't have a brain? Depending on your definition of "know," the answer may be yes. Researchers have shown that the slime mold, an organism without anything that resembles a nervous system (or, for that matter, individual cells), is capable of impressive feats of navigation. It can even link food sources in optimally spaced networks. Now, researchers have shown it's capable of filling its environment with indications of where it has already searched for food, allowing it to "remember" its past efforts and focus its attention on routes it hasn't explored.

And it does this all using, as the authors put it, "a thick mat of nonliving, translucent, extracellular slime." As you might expect, given the name.

Slime molds are odd creatures: organisms that have a nucleus and complex cells, but are evolutionarily distant from the multicellular animals and plants. When food is plentiful, they exist as single-celled, amoeba-like creatures that forage on the food. But once starvation sets in, the cells send out a signal that causes them to aggregate and fuse. This creates an organism that's visible to the naked eye and all a single cell, but filled with nuclei containing the genomes of many formerly individual cells. That turns out to be advantageous, because this collective can move more efficiently, and go about foraging for food. In the course of this foraging, the organism leaves behind a trail of slime.

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